DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 03/27/2026 has been entered.
This action is in response to the arguments filed on 02/12/2026. Claims 1-5, 7-14 and 16-20 are pending in the application and have been considered below.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-5, 7-14 and 16-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding Claim 1:
For Step 1, the claim is a method so it does recite a statutory category of invention.
For Step 2A, Prong 1:
The claim recites the limitation of “selecting a theme template matching the event type of the target event information from a theme template collection [stored in the local memory].” The selecting limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the selecting step from practically being performed in the human mind. This limitation is a mental process. (MPEP 2106.04(a)(2)(III)(C)).
The claim recites the limitation of “adding the entity information and the event type of the target event information into the theme template.” The adding limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the adding step from practically being performed in the human mind. This limitation is a mental process. (MPEP 2106.04(a)(2)(III)(C)).
The claim recites the limitation of “generate a theme of the pieces of event information
[on a display of the apparatus], wherein the theme template is a segment of text having positions to be filled” The generate limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the generate step from practically being performed in the human mind. This limitation is a mental process. (MPEP 2106.04(a)(2)(III)(C)).
The claim recites the limitation of “generate the theme of the pieces of event information, [on a display of the apparatus], wherein the theme template is a segment of text having positions to be filled; comprises: generating the theme of the pieces of event information by taking the entity information of the target event information as a subject of the segment of text and by taking the event type of the target event information as a predicate of the segment of text.” The generating limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the generating step from practically being performed in the human mind. This limitation is a mental process. (MPEP 2106.04(a)(2)(III)(C)).
For Step 2A, Prong 2, the claim recites additional elements: apparatus, local memory, display, deep learning, “obtaining a plurality of pieces of event information in an associated relation based on an event knowledge graph stored in a local memory of the apparatus,” “obtaining entity information and an event type of each piece of event information through deep learning, wherein in the event knowledge graph, the entity information and the event type are event nodes, and the associated relation is edge information between event nodes;” and “obtaining target event information having representative attributes from the pieces of event information.”
The "apparatus" is one of the four categories of patentable subject matter (along with process, machine, and composition of matter) and is used to describe a device or a system. MPEP 2106.05(f)
The “local memory” is a generic computer component that amounts to mere instructions to apply the abstract idea. See MPEP 2106.05(f).
The “display” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The recited “deep learning (i.e. as a type of machine learning that uses algorithms that are structured in layers)” amounts to mere instructions to apply an abstract idea under MPEP 2106.05 (f).
The “obtaining a plurality of pieces of event information in an associated relation based on an event knowledge graph stored in a local memory of the apparatus” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The “obtaining entity information and an event type of each piece of event information through deep learning, wherein in the event knowledge graph, the entity information and the event type are event nodes, and the associated relation is edge information between event nodes” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The “obtaining target event information having representative attributes from the pieces of event information” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
Step 2B
The additional element of “local memory,” “apparatus, “and “deep learning” do not amount to significantly more for the reasons set forth in step 2A above.
Under the Subject Matter Eligibility (SME), a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be reevaluated in Step 2B.
Here the “obtaining (i.e., .data gathering) a plurality of pieces of event information in an associated relation based on an event knowledge graph stored in a local memory of the apparatus” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by MPEP 2106.05(d)(II)(i).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
Here the “obtaining (i.e., .data gathering) entity information and an event type of each piece of event information through deep learning, wherein in the event knowledge graph, the entity information and the event type are event nodes, and the associated relation is edge information between event nodes” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by MPEP 2106.05(d)(II)(i).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
Here the “obtaining (i.e., .data gathering) target event information having representative attributes from the pieces of event information” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by MPEP 2106.05(d)(II)(i).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data.”
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of “local memory,” “apparatus, “and “deep learning” to perform the claim steps amount to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim is not patent eligible.
.
Regarding Claim 2:
Claim 2, which incorporates the rejection of claim 1, recites limitations such as “
“extracting a subgraph from the event knowledge graph, the subgraph comprising event nodes in an association relation” that are part of the abstract idea.
The claim recites an additional element: “stores an identifier of the event information, and an attribute of each event node comprises the entity information and the event type of the event information.”
The “stores an identifier of the event information, and an attribute of each event node comprises the entity information and the event type of the event information” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
Under the Subject Matter Eligibility (SME), a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be reevaluated in Step 2B.
The stores an identifier of the event information, and an attribute of each event node comprises the entity information and the event type of the event information” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93. MPEP 2106.05(d)(II)(iv)
iv. Storing and retrieving information in memory.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 3:
Claim 3, which incorporates the rejection of claim 2, recites limitations such as “
extracting a candidate subgraph from the event knowledge graph, the candidate subgraph comprising event nodes in an association relation” and “extracting the subgraph having a single-chain structure from the candidate subgraph when the
candidate subgraph comprises an event node having an outdegree equal to or greater than 2 or an indegree equal to or greater than 2” that are part of the abstract idea.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 4:
Claim 4, which incorporates the rejection of claim 2, recites further limitations such as “
determining subgraphs to be extracted from the event knowledge graph” that are part of the abstract idea.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 5:
Claim 5, which incorporates the rejection of claim 2, recites further limitations such as “
recognizing named entities in the event title of each piece of event information
and constructing an event node with the event information, the entity information and the event type of the event information, and constructing an edge between event nodes based on the association relation between corresponding event information to generate the event knowledge graph” that are part of the abstract idea.
The claim recites additional elements:
“obtaining the pieces of event information in the associated relation, each piece of event information comprising an event title and report content,” “classifying the report content of each piece of event information” and “obtain the event type of the event information.”
The “obtaining the pieces of event information in the associated relation, each piece of event information comprising an event title and report content” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The “classifying the report content of each piece of event information to obtain the event type of the event information” is a generic component to apply an abstract idea under 2106.05(f).
The additional elements “classifying the report content of each piece of event information to obtain the event type of the event information” and “generate the event knowledge graph” do not amount to significantly more for the reasons set forth in step 2A above.
Additionally, under the Subject Matter Eligibility (SME), a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be reevaluated in Step 2B.
Here the “obtaining (i.e., .data gathering) the pieces of event information in the associated relation, each p1ece of event information comprising an event title and report content” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by MPEP 2106.05(d)(II)(i).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
Here the step “obtain the event type of the event information” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by MPEP 2106.05(d)(II)(i).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of “classifying the report content of each piece of event information to obtain the event type of the event information” to perform the claim steps amount to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 7:
Claim 7, which incorporates the rejection of claim 1, recites further limitations such as “
sorting the pieces of event information based on an occurrence time sequence of the pieces of event information” and selecting a first piece or a last piece from pieces of sorted event information as the target event information” that are part of the abstract idea.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 8:
Claim 8, which incorporates the rejection of claim 7, recites further limitations such as “
calculating a similarity between every two pieces of event information; and
removing one of two pieces of event information, when the similarity between the two pieces of event information exceeds a preset similarity threshold” that are part of the abstract idea.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 9:
Claim 9, which incorporates the rejection of claim 1, recites further limitations such as “
“counting the number of pieces of different entity information and the number of different event types of the pieces of event information; determining a first theme modifier word for each piece of different entity information, when the number of pieces of the different entity information exceeds a preset threshold; determining a second theme modifier word for each different event type, when the number of different event types exceeds the preset threshold; and adding the entity information, the event type, the first theme modifier word and the second theme modifier word of the target event information into the theme template to generate the theme of the pieces of event information” that are part of the abstract idea.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 10:
For Step 1, the claim is an electronic device so it does recite a statutory category of invention.
For Step 2A, Prong 1:
The claim recites the limitation of “select a theme template matching the event type of the target event information from a theme template collection [stored in the local memory].” The select limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the select step from practically being performed in the human mind. This limitation is a mental process. (MPEP 2106.04(a)(2)(III)(C)).
The claim recites the limitation of “add the entity information and the event type of the target event information into the theme template.” The add limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the add step from practically being performed in the human mind. This limitation is a mental process. (MPEP 2106.04(a)(2)(III)(C)).
The claim recites the limitation of “generate a theme of the pieces of event information [on a display of the apparatus], wherein the theme template is a segment of text having positions to be filled.” The “generate” limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the generate step from practically being performed in the human mind. This limitation is a mental process. (MPEP 2106.04(a)(2)(III)(C)).
The claim recites the limitation of “generate the theme of the pieces of event information by taking the entity information of the target event information as a subject of the
segment of text and by taking the event type of the target event information as a predicate of the segment of text.” The generate limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the generate step from practically being performed in the human mind. This limitation is a mental process. (MPEP 2106.04(a)(2)(III)(C)).
For Step 2A, Prong 2, the claim recites additional elements: processor, memory, deep learning, “obtain a plurality of pieces of event information in an associated relation based on an event knowledge graph stored in a local memory of the apparatus,” “obtain entity information and an event type of each piece of event information through deep learning, wherein in the event knowledge graph, the entity information and the event type are event nodes, and the associated relation is edge information between event nodes;” “obtain target event information having representative attributes from the pieces of event information” and display
The processor is recited at a high level of generality, i.e., as a generic processor performing a generic computer function of processing data. This generic processor limitation is no more than mere instructions to apply the exception using a generic computer component. (MPEP 2106.05(f)).
The “memory” is a generic computer component that amount to mere instructions to apply the abstract idea. See MPEP 2106.05(f).
The recited “deep learning” (i.e. “a type of machine learning that uses algorithms that are structured in layers”) amounts to mere instructions to apply an abstract idea under MPEP 2106.05 (f).
The “obtain a plurality of pieces of event information in an associated relation based on an event knowledge graph stored in a local memory of the electronic device” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The “obtain entity information and an event type of each piece of event
information based on an event knowledge graph through deep learning, wherein in the event knowledge graph, the entity information and the event type are event nodes, and the associated relation is edge information between event nodes” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The “obtain target event information having representative attributes from the pieces of event information” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The “display” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
Step 2B
The additional elements: processor, memory and deep learning do not amount to significantly more for the reasons set forth in step 2A above.
Additionally, under the Subject Matter Eligibility (SME), a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be reevaluated in Step 2B.
Here the “obtain (i.e., .data gathering) a plurality of pieces of event information in an associated relation based on an event knowledge graph stored in a local memory of the electronic device” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by MPEP 2106.05(d)(II)(i).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data.”
Here the “obtain (i.e., .data gathering) entity information and an event type of each piece of event information…wherein in the event knowledge graph, the entity information and the event type are event nodes, and the associated relation is
edge information between event nodes” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by MPEP 2106.05(d)(II)(i).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data.”
Here the “obtain (i.e., .data gathering) target event information having representative attributes from the pieces of event information” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by MPEP 2106.05(d)(II)(i).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements “processor, memory and deep learning “to perform the claim steps amount to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 11:
Claim 11, which incorporates the rejection of claim 10, recites limitations such as “extract a subgraph from the event knowledge graph, the subgraph comprising event nodes in an association relation” that are part of the abstract idea.
The claim recites an additional element: “stores an identifier of the event information, and an attribute of each event node comprises the entity information and the event type of the event information.”
The “stores an identifier of the event information, and an attribute of each event node comprises the entity information and the event type of the event information” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
Under the Subject Matter Eligibility (SME), a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be reevaluated in Step 2B.
The stores an identifier of the event information, and an attribute of each event node comprises the entity information and the event type of the event information” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93. MPEP 2106.05(d)(II)(iv)
iv. Storing and retrieving information in memory.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 12:
Claim 12, which incorporates the rejection of claim 11, recites further limitations such as
“extract a candidate subgraph from the event knowledge graph, the candidate subgraph comprising event nodes in an association relation” and “extract the subgraph having a single-chain structure from the candidate subgraph when the candidate subgraph comprises an event node having an outdegree equal to or greater than 2 or an indegree equal to or greater than 2” that are part of the abstract idea.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 13:
Claim 13, which incorporates the rejection of claim 11, recites further limitations such as “determine subgraphs to be extracted from the event knowledge graph; and extract the subgraph when the number of nodes in the subgraph is equal to or greater than a preset number, and/or a total popularity degree of the event nodes included in the subgraph is equal to or greater than a preset popularity degree” that are part of the abstract idea.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 14:
Claim 14, which incorporates the rejection of claim 11, recites further limitations such as “recognizing named entities in the event title of each piece of event information
and constructing an event node with the event information, the entity information and the event type of the event information, and constructing an edge between event nodes based on the association relation between corresponding event information to generate the event knowledge graph” that are part of the abstract idea” that are part of the abstract idea.
The claim recites additional elements: “obtain the pieces of event information in the associated relation, each piece of event information comprising an event title and report content” and “classify the report content of each piece of event information” and “obtain the event type of the event information.”
The “classify the report content of each piece of event information to obtain the event type of the event information” is a generic component to apply an abstract idea under 2106.05(f).
The additional element “classify the report content of each piece of event information to obtain the event type of the event information” does not amount to significantly more for the reasons set forth in step 2A above.
Additionally, under the Subject Matter Eligibility (SME), a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be reevaluated in Step 2B.
Here the “obtain (i.e., .data gathering) the pieces of event information in the associated relation, each p1ece of event information comprising an event title and report content” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by MPEP 2106.05(d)(II)(i).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element “classify the report content of each piece of event information to obtain the event type of the event information” to perform the claim steps amount to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 16:
Claim 16, which incorporates the rejection of claim 10, recites further limitations such as “sort the pieces of event information based on an occurrence time sequence of the pieces of event information” and select a first piece or a last piece from pieces of sorted event information as the target event information” that are part of the abstract idea.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 17:
Claim 17, which incorporates the rejection of claim 16, recites further limitations such as “calculate a similarity between every two pieces of event information; and
remove one of two pieces of event information, when the similarity between the two pieces of event information exceeds a preset similarity threshold” that are part of the abstract idea.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 18:
Claim 18, which incorporates the rejection of claim 10, recites further limitations such as “count the number of pieces of different entity information and the number of different event types of the pieces of event information; determine a first theme modifier word for each piece of different entity information, when the number of pieces of the different entity information exceeds a preset threshold; determine a second theme modifier word for each different event type, when the number of different event types exceeds the preset threshold; and add the entity information, the event type, the first theme modifier word and the second theme modifier word of the target event information into the theme template to generate the theme of the pieces of event information” that are part of the abstract idea.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 19:
For Step 1, the claim is a non-transitory computer-readable storage medium so it does recite a statutory category of invention.
For Step 2A, Prong 1:
The claim recites the limitation of “selecting a theme template matching the event type of the target event information from a theme template collection.” The selecting limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the selecting step from practically being performed in the human mind. This limitation is a mental process. (MPEP 2106.04(a)(2)(III)(C)).
The claim recites the limitation of “adding the entity information and the event type of the target event information into the theme template.” The adding limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the adding step from practically being performed in the human mind. This limitation is a mental process. (MPEP 2106.04(a)(2)(III)(C)).
The claim recites the limitation of “generate a theme of the pieces of event information…wherein the theme template is a segment of text having positions to be filled. The generate limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the generate step from practically being performed in the human mind. This limitation is a mental process. (MPEP 2106.04(a)(2)(III)(C)).
The claim recites the limitation of “generating the theme of the pieces of event information by taking the entity information of the target event information as a subject of the theme template and by taking the event type of the target event information as a predicate of the theme template.” The generating limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the generating step from practically being performed in the human mind. This limitation is a mental process. (MPEP 2106.04(a)(2)(III)(C)).
For Step 2A, Prong 2, the claim recites additional elements: computer, “local memory,” “display,” “obtaining a plurality of pieces of event information in an associated relation based on an event knowledge graph stored… wherein in the event knowledge graph, the entity information and the event type are event nodes, and the associated relation is edge information between event nodes,” “obtaining entity information and an event type of each piece of event information” and “obtaining target event information having representative attributes from the pieces of event information.”
The “computer” is a generic computer component that amounts to mere instructions to apply the abstract idea. See MPEP 2106.05(f).
The “local memory” is a generic computer component that amounts to mere instructions to apply the abstract idea. See MPEP 2106.05(f).
The “display” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The “obtaining a plurality of pieces of event information in an associated relation
based on an event knowledge graph” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The “obtaining entity information and an event type of each piece of event information...
wherein in the event knowledge graph, the entity information and the event type are event nodes, and the associated relation is edge information between event nodes” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The “obtaining target event information having representative attributes from the pieces of event information” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
Step 2B
The additional elements of “computer” and “local memory” do not amount to significantly more for the reasons set forth in step 2A above.
Additionally, under the Subject Matter Eligibility (SME), a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be reevaluated in Step 2B.
Here the “obtaining (i.e., .data gathering) a plurality of pieces of event information in an associated relation based on an event knowledge graph …” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by MPEP 2106.05(d)(II)(i).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
Here the “obtaining (i.e., data gathering) entity information and an event type of each piece of event information…wherein in the event knowledge graph, the entity information and the event type are event nodes, and the associated relation is edge information between event nodes”” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by MPEP 2106.05(d)(II)(i).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
Here the “obtaining (i.e., .data gathering) target event information having representative attributes from the pieces of event information” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by MPEP 2106.05(d)(II)(i).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of “computer” and “local memory” to perform the claim steps amount to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 20:
Claim 20, which incorporates the rejection of claim 19, recites further limitations such as “extracting a subgraph from the event knowledge graph, the subgraph comprising event nodes in an association relation” that are part of the abstract idea.
The claim recites an additional element:
“stores an identifier of the event information, and an attribute of each event node comprises the entity information and the event type of the event information.”
The “stores an identifier of the event information, and an attribute of each event node comprises the entity information and the event type of the event information” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
Under the Subject Matter Eligibility (SME), a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be reevaluated in Step 2B.
The stores an identifier of the event information, and an attribute of each event node comprises the entity information and the event type of the event information” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93. MPEP 2106.05(d)(II)(iv)
iv. Storing and retrieving information in memory.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1, 10 and 19 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention:
Claim 1:
obtaining a plurality of pieces of event information in an associated relation based on an event knowledge graph stored in a local memory of the apparatus,
selecting a theme template matching the event type of the target event information from a theme template collection stored in the local memory.
Claim 10:
obtain a plurality of pieces of event information in an associated relation based on an event knowledge graph stored in a local memory of the apparatus,
select a theme template matching the event type of the target event information from a theme template collection stored in the local memory.
Claim 19:
obtaining a plurality of pieces of event information in an associated relation based on an event knowledge graph stored in a local memory of the apparatus,
selecting a theme template matching the event type of the target event information from a theme template collection stored in the local memory.
On page 3, lines 20-21, the specification (original disclosure) recites
At block S110, a plurality of pieces of event information in an associated relation are obtained, and entity information and an event type of each event information is obtained.
On page 10, lines 26-27, the specification (original disclosure) recites:
At block S430, a theme template matching the event type of the target event information is selected from a theme template collection.
Therefore, there is no support for the newly underlined amended features:
obtaining a plurality of pieces of event information in an associated relation based on an event knowledge graph stored in a local memory of the apparatus,
selecting a theme template matching the event type of the target event information from a theme template collection stored in the local memory.
The specification (original disclosure) does not provide any support for “segment of text” recited below:
…as a subject of the segment of text and by taking the event type of the target event information as a predicate of the segment of text.
Dependent claims 2-5, 7-14 and 16-20 inherited the deficiencies of the parent claim. Therefore, they are rejected under 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph.
Claim Objections
Claim 1 is objected to because of the following informalities:” … from tine pieces of event information.” It should recite:” … from the pieces of event information.” Appropriate correction is required.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 10 and 19 are rejected under 35 U.S.C. 103 as being unpatentable Carbune et al. (US 2022/0138591 A1, hereinafter referred to as Carbune), in view of Clark et al. (US 2017/0161311 A1, hereinafter referred to as Clark), and further in view of Shaer (US 2002/0128934 A1, hereinafter referred to as Shaer), and Mithal et al. (US 2013/0144748 A1, hereinafter referred to as Mithal), and Pahud et al. (US 2006/0217979 A1, hereinafter referred to as Pahud).
As to claim 1, Carbune teaches method for generating an event theme, performed by an apparatus, comprising:
obtaining a plurality of pieces of event information in an associated relation
based on an event knowledge graph [stored in a local memory of the apparatus]
(paragraphs [0006] If enough queries, e.g., a cluster of semantically related queries, evidence a newly-developing event, that may trigger analysis of multiple live data streams, such as social media posts, to obtain information to populate an event-specific knowledge graph. As another example, multiple live streams such as social media posts may be analyzed on an ongoing basis. Similar to clusters of semantically-related queries, if a sufficient number or cluster of semantically-related posts are identified, that may evidence a newly-developing event; [0045] Based on information obtained from query monitor 132 and/or live stream monitor 134, provisional knowledge graph manager 136 may be configured to build, manage, and/or maintain one or more event-specific provisional knowledge graphs 139), and obtaining entity information and an event type of each piece of event information through deep learning (paragraph [0075], data indicative of its constituent entities/edges may be applied as input across one or event type machine learning models, such as a support vector machine, neural network, graph neural network, graph convolutional network, graph attention network, etc. Such a machine learning model may be trained to generate output that predicts an event type of the event. For example, a neural network may be trained using training examples that each include a plurality of features extracted from an event of a known event type. Each training example may be labeled with a corresponding event type), wherein in the event knowledge graph, the entity information and the event type are event nodes, and the associated relation is edge information between event nodes (paragraphs [0004] For example, as a newsworthy event unfolds, live event streams such as social media posts from witnesses or others purporting to have knowledge of the event may be analyzed to identify one or more entities associated with the event. Although the event itself may eventually be represented in the general-purpose knowledge graph as an entity-node, there may be some delay before the general-purpose knowledge graph is updated; [0062] - [0064], event-specific provisional knowledge graph 139 includes one or more additional nodes or edges, such as developing event node 450, that are not found in general-purpose knowledge graph 138. These new nodes and/or edges may convey a relationship between the identified one or more entities and the developing event);
obtaining target event information having representative attributes from the pieces of event information (paragraph [0034] In some implementations, general-purpose knowledge graph 138 may include nodes that represent known entities (and in some cases, entity attributes), as well as edges that connect the nodes and represent relationships between the entities. For example, a "banana" node may be connected (e.g., as a child) to a "fruit" node," which in turn may be connected (e.g., as a child) to "produce" and/or "food" nodes. As another example, a restaurant called "Hypothetical Cafe" may be represented by a node that also includes attributes such as its address, type of food served, hours, contact information, etc. The "Hypothetical Cafe" node may in some implementations be connected by an edge (e.g., representing a child-to-parent relationship) to one or more other nodes, such as a "restaurant" node, a "business" node, a node representing a city and/or state in which the restaurant is located, and so
forth);
selecting a theme template matching the event type of the target event information from a theme template collection [stored in the local memory]
(paragraphs [0011] In various implementations, determining the event type comprises determining that the one or more additional nodes or edges that are not found in the general-purpose knowledge graph match an event type template associated with the event type; [0074] This analysis may include comparing the data to one or more "event type templates." An event type template may be associated (interpreted as “matching by Examiner) with a particular event type, e.g., protest, riot, disaster, sporting event, concert, political rally, criminal act, terrorist attack, etc. The event type template may include "slots" associated with expected event type data points that are typically associated with the particular event type. For example, a sporting event type template may include slots for "scores," "players," "coaches," "attendance," "teams," and other data points typically found in social media posts related to sporting events. A "building fire" event type template may include slots for "fire," flames," "smoke," "firetrucks," "EMS," "hoses," and other data points typically found in social media posts related to building fires), wherein the theme template is a segment of text having positions to be filled (paragraphs [0074]-[0075] An event type template may be associated with a particular event type, e.g., protest, riot, disaster, sporting event, concert, political rally, criminal act, terrorist attack, etc. The event type template may include "slots" associated with expected event type data points that are typically associated with the particular event type. For example, a sporting event type template may include slots for "scores," "players," "coaches," "attendance," "teams," and other data points typically found in social media posts related to sporting events. A "building fire" event type template may include slots for "fire," flames," "smoke," "firetrucks," "EMS," "hoses," and other data points typically found in social media posts related to building fires; wherein Examiner “slots “as “positions to be filled”).
However, Carbune fails to explicitly teach:
an event knowledge graph stored in a local memory of the apparatus;
a theme template collection stored in the local memory;
adding the entity information and the event type of the target event information into the theme template to generate a theme of the pieces of event information
on a display of the apparatus, [wherein the theme template is a segment of text having positions to be filled];
wherein adding the entity information and the event type of the target event information into the theme template to generate the theme of the pieces of event information comprises: generating the theme of the pieces of event information by taking the entity information of the target event information as a subject of the segment of text and by taking the event type of the target event information as a predicate of the segment of text.
Clark, in combination with Carbune, teaches:
an event knowledge graph stored in a local memory of the apparatus (paragraph [0067] For example, knowledge graphs may be generated by third parties, received by the computer system, and then stored in memory until the knowledge graph is needed; [0100], apparatus (systems)).
It would have been obvious to one of ordinary skill in the art before the effective filing of
the claimed invention to modify the system of Carbune to add a knowledge graph stored in a local memory to the system of Carbune as taught by Clark, above. The modification would have been obvious because one of ordinary skill would be motivated to have the knowledge graph stored in memory until the knowledge graph is needed, as suggested by Clark, ([0067]).
However, Carbune and Clark fail to explicitly teach:
a theme template collection stored in the local memory;
adding the entity information and the event type of the target event information into the theme template to generate a theme of the pieces of event information
on a display of the apparatus, [wherein the theme template is a segment of text having positions to be filled];
wherein adding the entity information and the event type of the target event information into the theme template to generate the theme of the pieces of event information comprises: generating the theme of the pieces of event information by taking the entity information of the target event information as a subject of the segment of text and by taking the event type of the target event information as a predicate of the segment of text.
Shaer, in combination with Carbune and Clark, teaches:
a theme template collection stored in the local memory (Abstract: different templates (interpreted by Examiner as theme template collection) with prices are stored in memory).
It would have been obvious to one of ordinary skill in the art before the effective filing of
the claimed invention to modify the combination system of Carbune and Clark to add a template collection stored in a local memory to the combination system of Carbune and Clark as taught by Shaer, above. The modification would have been obvious to have
the best possible service having highest quality and lowest price within lesser time, , as suggested by Shaer, ([0231]).
However, Carbune, Clark and Shaer fail to explicitly teach:
adding the entity information and the event type of the target event information into the theme template to generate a theme of the pieces of event information
on a display of the apparatus, [wherein the theme template is a segment of text having positions to be filled];
wherein adding the entity information and the event type of the target event information into the theme template to generate the theme of the pieces of event information comprises: generating the theme of the pieces of event information by taking the entity information of the target event information as a subject of the segment of text and by taking the event type of the target event information as a predicate of the segment of text.
Mithal, in combination with Carbune, Clark and Shaer teaches:
adding the entity information and the event type of the target event information into the theme template to generate a theme of the pieces of event information on a display of the apparatus (paragraphs [0089]-[0091] Two exemplary birthday templates are presented in FIG. 4, FIG. 5 and FIG.7 which show round white plates having areas for customization where a user or potential customer could insert his/her own message or custom text (Examiner interprets a user or potential customer own message or custom text as the entity information; insert as adding; and 21st birthday as event type; theme templates to include a theme template). One of the main objectives of providing theme templates is to provide the user with the convenience of quickly selecting a basic product style which can be customized by the user by simply providing textual input), [wherein the theme template is a segment of text having positions to be filled])..
It would have been obvious to one of ordinary skill in the art before the effective filing of
the claimed invention to modify the system of Bhageria to add theme template to the system of Bhageria, as taught by Mithal, above. The modification would have been obvious because one of ordinary skill would be motivated to customize their specific selection using standard templates for a theme, as suggested by Mithal, ([0090]).
However, Carbune, Clark, Shaer and Mithal fail to explicitly teach:
wherein adding the entity information and the event type of the target event information into the theme template to generate the theme of the pieces of event information comprises: generating the theme of the pieces of event information by taking the entity information of the target event information as a subject of the segment of text and by taking the event type of the target event information as a predicate of the segment of text.
Pahud, in combination with Carbune, Clark, Shaer and Mithal, teaches:
wherein adding the entity information and the event type of the target event information into the theme template to generate the theme of the pieces of event information comprises: generating the theme of the pieces of event information by taking the entity information of the target event information as a subject of the segment of text and by taking the event type of the target event information as a predicate of the segment of text (paragraphs [0060]- [0062] As shown in FIG. 7, a first sentence 710 (sentence 1) is entered: Once upon a time a dragon flew over a beach (interpreted by Examiner as segment of text). Note that as indicated in the figure, a period is not yet entered and no scene is rendered in the viewing window 720. After entering the period (end-of-sentence indicator), an animated Scene of the dragon flying over a beach can be seen in the viewing window 810 as demonstrated in the screen capture 800 in FIG. 8. As a guide, the sentence being illustrated can be viewed in the window as well 810. Examiner interprets “a dragon” as the subject of the theme template. “over a beach” as the predicate of the theme template”).
It would have been obvious to one of ordinary skill in the art before the effective filing of
the claimed invention to modify the combination system of Carbune, Clark, Shaer and Mithal to add theme template to the combination system of Carbune, Clark, Shaer and Mithal, as taught by Pahud, above. The modification would have been obvious because one of ordinary skill would be motivated to customize their specific selection using standard templates for a theme, as suggested by Pahud, ([0005]).
As to claim 10, Carbune teaches an electronic device, comprising:
at least one processor (paragraph [0012], processors); and
a memory communicatively connected with the at least one processor (paragraph [0101], memory); wherein,
the memory is configured to store instructions executable by the at least one processor, and when the instructions are executed by the at least one processor (paragraphs [0012]), the at least one processor is configured to:
obtain a plurality of pieces of event information in an associated relation
based on an event knowledge graph [stored in a local memory of the electronic device] (paragraphs [0006] If enough queries, e.g., a cluster of semantically related queries, evidence a newly-developing event, that may trigger analysis of multiple live data streams, such as social media posts, to obtain information to populate an event-specific knowledge graph. As another example, multiple live streams such as social media posts may be analyzed on an ongoing basis. Similar to clusters of semantically-related queries, if a sufficient number or cluster of semantically-related posts are identified, that may evidence a newly-developing event; [0045] Based on information obtained from query monitor 132 and/or live stream monitor 134, provisional knowledge graph manager 136 may be configured to build, manage, and/or maintain one or more event-specific provisional knowledge graphs 139), and obtain entity information and an event type of each piece of event information through deep learning (paragraph [0075], data indicative of its constituent entities/edges may be applied as input across one or event type machine learning models, such as a support vector machine, neural network, graph neural network, graph convolutional network, graph attention network, etc. Such a machine learning model may be trained to generate output that predicts an event type of the event. For example, a neural network may be trained using training examples that each include a plurality of features extracted from an event of a known event type. Each training example may be labeled with a corresponding event type), wherein in the event knowledge graph, the entity information and the event type are event nodes, and the associated relation is edge information between event nodes (paragraphs [0004] For example, as a newsworthy event unfolds, live event streams such as social media posts from witnesses or others purporting to have knowledge of the event may be analyzed to identify one or more entities associated with the event. Although the event itself may eventually be represented in the general-purpose knowledge graph as an entity-node, there may be some delay before the general-purpose knowledge graph is updated; [0062] - [0064], event-specific provisional knowledge graph 139 includes one or more additional nodes or edges, such as developing event node 450, that are not found in general-purpose knowledge graph 138. These new nodes and/or edges may convey a relationship between the identified one or more entities and the developing event);
obtain target event information having representative attributes from the pieces of event information (paragraph [0034] In some implementations, general-purpose knowledge graph 138 may include nodes that represent known entities (and in some cases, entity attributes), as well as edges that connect the nodes and represent relationships between the entities. For example, a "banana" node may be connected (e.g., as a child) to a "fruit" node," which in turn may be connected (e.g., as a child) to "produce" and/or "food" nodes. As another example, a restaurant called "Hypothetical Cafe" may be represented by a node that also includes attributes such as its address, type of food served, hours, contact information, etc. The "Hypothetical Cafe" node may in some implementations be connected by an edge (e.g., representing a child-to-parent relationship) to one or more other nodes, such as a "restaurant" node, a "business" node, a node representing a city and/or state in which the restaurant is located, and so
forth);
select a theme template matching the event type of the target event information from a theme template collection [stored in the local memory]
(paragraphs [0011] In various implementations, determining the event type comprises determining that the one or more additional nodes or edges that are not found in the general-purpose knowledge graph match an event type template associated with the event type; [0074] This analysis may include comparing the data to one or more "event type templates." An event type template may be associated (interpreted as “matching by Examiner) with a particular event type, e.g., protest, riot, disaster, sporting event, concert, political rally, criminal act, terrorist attack, etc. The event type template may include "slots" associated with expected event type data points that are typically associated with the particular event type. For example, a sporting event type template may include slots for "scores," "players," "coaches," "attendance," "teams," and other data points typically found in social media posts related to sporting events. A "building fire" event type template may include slots for "fire," flames," "smoke," "firetrucks," "EMS," "hoses," and other data points typically found in social media posts related to building fires), wherein the theme template is a segment of text having positions to be filled (paragraphs [0074]-[0075] An event type template may be associated with a particular event type, e.g., protest, riot, disaster, sporting event, concert, political rally, criminal act, terrorist attack, etc. The event type template may include "slots" associated with expected event type data points that are typically associated with the particular event type. For example, a sporting event type template may include slots for "scores," "players," "coaches," "attendance," "teams," and other data points typically found in social media posts related to sporting events. A "building fire" event type template may include slots for "fire," flames," "smoke," "firetrucks," "EMS," "hoses," and other data points typically found in social media posts related to building fires; wherein Examiner “slots “as positions to be filled”).
However, Carbune fails to explicitly teach:
an event knowledge graph stored in a local memory of the electronic device;
a theme template collection stored in the local memory;
add the entity information and the event type of the target event information into the theme template to generate a theme of the pieces of event information
on a display of the electronic device, [wherein the theme template is a segment of text having positions to be filled];
wherein the processor is configured to generate the theme of the pieces of event information by taking the entity information of the target event information as a subject of the segment of text and by taking the event type of the target event information as a predicate of the segment of text.
Clark, in combination with Carbune, teaches:
an event knowledge graph stored in a local memory of the electronic device (paragraph [0067] For example, knowledge graphs may be generated by third parties, received by the computer system, and then stored in memory until the knowledge graph is needed; [0100], apparatus (systems))
It would have been obvious to one of ordinary skill in the art before the effective filing of
the claimed invention to modify the system of Carbune to add a knowledge graph stored in a local memory to the system of Carbune as taught by Clark, above. The modification would have been obvious because one of ordinary skill would be motivated to have the knowledge graph stored in memory until the knowledge graph is needed, as suggested by Clark, ([0067]).
However, Carbune and Clark fail to explicitly teach:
a theme template collection stored in the local memory;
add the entity information and the event type of the target event information into the theme template to generate a theme of the pieces of event information
on a display of the electronic device, [wherein the theme template is a segment of text having positions to be filled];
wherein the processor is configured to generate the theme of the pieces of event information by taking the entity information of the target event information as a subject of the segment of text and by taking the event type of the target event information as a predicate of the segment of text.
Shaer, in combination with Carbune and Clark, teaches:
a theme template collection stored in the local memory (Abstract: different templates (interpreted by Examiner as theme template collection) with prices are stored in memory).
It would have been obvious to one of ordinary skill in the art before the effective filing of
the claimed invention to modify the combination system of Carbune and Clark to add a template collection stored in a local memory to the combination system of Carbune and Clark as taught by Shaer, above. The modification would have been obvious to have
the best possible service having highest quality and lowest price within lesser time, , as suggested by Shaer, ([0231]).
However, Carbune, Clark and Shaer fail to explicitly teach:
add the entity information and the event type of the target event information into the theme template to generate a theme of the pieces of event information
on a display of the electronic device, [wherein the theme template is a segment of text having positions to be filled];
wherein the processor is configured to generate the theme of the pieces of event information by taking the entity information of the target event information as a subject of the segment of text and by taking the event type of the target event information as a predicate of the segment of text.
Mithal, in combination with Carbune, Clark and Shaer teaches:
add the entity information and the event type of the target event information into the theme template to generate a theme of the pieces of event information on a display of the apparatus (paragraphs [0089]-[0091] Two exemplary birthday templates are presented in FIG. 4, FIG. 5 and FIG.7 which show round white plates having areas for customization where a user or potential customer could insert his/her own message or custom text (Examiner interprets a user or potential customer own message or custom text as the entity information; insert as adding; and 21st birthday as event type; theme templates to include a theme template). One of the main objectives of providing theme templates is to provide the user with the convenience of quickly selecting a basic product style which can be customized by the user by simply providing textual input), [wherein the theme template is a segment of text having positions to be filled]).
It would have been obvious to one of ordinary skill in the art before the effective filing of
the claimed invention to modify the system of Bhageria to add theme template to the system of Bhageria, as taught by Mithal, above. The modification would have been obvious because one of ordinary skill would be motivated to customize their specific selection using standard templates for a theme, as suggested by Mithal, ([0090]).
However, Carbune, Clark, Shaer and Mithal fail to explicitly teach:
wherein the processor is configured to generate the theme of the pieces of event information by taking the entity information of the target event information as a subject of the segment of text and by taking the event type of the target event information as a predicate of the segment of text.
Pahud, in combination with Carbune, Clark, Shaer and Mithal, teaches:
wherein the processor is configured to generate the theme of the pieces of event information by taking the entity information of the target event information as a subject of the segment of text and by taking the event type of the target event information as a predicate of the segment of text (paragraphs [0060]- [0062] As shown in FIG. 7, a first sentence 710 (sentence 1) is entered: Once upon a time a dragon flew over a beach (interpreted by Examiner as segment of text). Note that as indicated in the figure, a period is not yet entered and no scene is rendered in the viewing window 720. After entering the period (end-of-sentence indicator), an animated Scene of the dragon flying over a beach can be seen in the viewing window 810 as demonstrated in the screen capture 800 in FIG. 8. As a guide, the sentence being illustrated can be viewed in the window as well 810. Examiner interprets “a dragon” as the subject of the theme template. “over a beach” as the predicate of the theme template”).
It would have been obvious to one of ordinary skill in the art before the effective filing of
the claimed invention to modify the combination system of Carbune, Clark, Shaer and Mithal to add theme template to the combination system of Carbune, Clark, Shaer and Mithal, as taught by Pahud, above. The modification would have been obvious because one of ordinary skill would be motivated to customize their specific selection using standard templates for a theme, as suggested by Pahud, ([0005]).
Claims 2, 11 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Carbune et al. (US 2022/0138591 A1, hereinafter referred to as Carbune), in view of Clark et al. (US 2017/0161311 A1, hereinafter referred to as Clark), and further in view of Shaer (US 2002/0128934 A1, hereinafter referred to as Shaer), and Mithal et al. (US 2013/0144748 A1, hereinafter referred to as Mithal), and Pahud et al. (US 2006/0217979 A1, hereinafter referred to as Pahud), and Choe et al. (US 2014/0324864 A1, hereinafter referred to as Choe).
As to claim 2, which incorporates the rejection of claim 1, of Carbune, Clark, Shaer, Mithal and Pahud teach wherein obtaining the plurality of pieces of event information in the associated relation, and obtaining the entity information and the event type of each piece of event information.
However, Carbune, Clark, Shaer, Mithal and Pahud fail to explicitly teach:
extracting a subgraph from an event knowledge graph, the subgraph comprising event nodes in an association relation, wherein each event node stores an identifier of the event information, and an attribute of each event node comprises the entity information and the event type of the event information.
Choe, in combination with Carbune, Clark, Shaer, Mithal and Pahud, teaches:
extracting a subgraph from an event knowledge graph, the subgraph comprising event nodes in an association relation, wherein each event node stores an identifier of the event information, and an attribute of each event node comprises the entity information and the event type of the event information (paragraphs [0097]-[0099] A plurality of these, such as all possible two-node subgraphs, or a subset of possible two-node subgraphs of the relational graph may be extracted. In certain embodiments, a plurality of subgraphs of different orders are extracted, and after a set of subgraphs is extracted, each extracted subgraph is indexed and saved in a subgraph feature vocabulary; [0111], subgraphs may be extracted from a database that stores the first relational graph. The number of subgraphs obtained may include p subgraphs. In one embodiment, for example, a plurality of I-node subgraphs (e.g., all of the I-node subgraphs in the first relational graph) and a plurality of 2-node subgraphs (e.g., all of the 2-node subgraphs in the relational graph) may be obtained from the first relational graph. Each obtained subgraph may be indexed (Examiner interprets indexed as identifier), for example in a database; [0122] and [0133]).
It would have been obvious to one of ordinary skill in the art before the effective filing of
the claimed invention to modify the combination system of Carbune, Clark, Shaer, Mithal and Pahud A to add subgraph extraction to the combination system of Carbune, Clark, Shaer, Mithal and Pahud, as taught by Choe, above. The modification would have been obvious because one of ordinary skill would be motivated to have extracted subgraphs from each relational graph and dimension reduction may be performed on the subgraphs to reduce the complexity of the search that resources need to perform the search, as suggested by Choe, ([0119]).
As to claim 11, which incorporates the rejection of claim 10, Carbune, Clark, Shaer, Mithal and Pahud fail to explicitly teach wherein the processor is further configured to:
extract a subgraph from an event knowledge graph, the subgraph comprising event nodes in an association relation, wherein each event node stores an identifier of the event information, and an attribute of each event node comprises the entity information and the event type of the event information.
Choe, in combination with Carbune, Clark, Shaer, Mithal and Pahud, teaches:
extract a subgraph from an event knowledge graph, the subgraph comprising event nodes in an association relation, wherein each event node stores an identifier of the event information, and an attribute of each event node comprises the entity information and the event type of the event information (paragraphs [0097]- [0099] A plurality of these, such as all possible two-node subgraphs, or a subset of possible two-node subgraphs of the relational graph may be extracted. In certain embodiments, a plurality of subgraphs of different orders are extracted, and after a set of subgraphs is extracted, each extracted subgraph is indexed and saved in a subgraph feature vocabulary; [0111], subgraphs may be extracted from a database that stores the first relational graph. The number of subgraphs obtained may include p subgraphs. In one embodiment, for example, a plurality of I-node subgraphs (e.g., all of the I-node subgraphs in the first relational graph) and a plurality of 2-node subgraphs (e.g., all of the 2-node subgraphs in the relational graph) may be obtained from the first relational graph. Each obtained subgraph may be indexed (Examiner interprets indexed as identifier), for example in a database; [0122] and [0133].).
It would have been obvious to one of ordinary skill in the art before the effective filing of
the claimed invention to modify the combination system Carbune, Clark, Shaer, Mithal and Pahud to add subgraph extraction to the combination system of Carbune, Clark, Shaer, Mithal and Pahud, as taught by Choe, above. The modification would have been obvious because one of ordinary skill would be motivated to have extracted subgraphs from each relational graph and dimension reduction may be performed on the subgraphs to reduce the complexity of the search that resources need to perform the search, as suggested by Choe, ([0119]).
As to claim 20, which incorporates the rejection of claim 19, Carbune, Clark, Shaer, Mithal and Pahud teach wherein obtaining the plurality of pieces of event information in the associated relation, and obtaining the entity information and the event type of each piece of event information.
However, Carbune, Clark, Shaer, Mithal and Pahud fail to explicitly teach:
extracting a subgraph from an event knowledge graph, the subgraph comprising event nodes in an association relation, wherein each event node stores an identifier of the event information, and an attribute of each event node comprises the entity information and the event type of the event information.
Choe, in combination with Carbune, Clark, Shaer, Mithal and Pahud, teaches:
extracting a subgraph from an event knowledge graph, the subgraph comprising event nodes in an association relation, wherein each event node stores an identifier of the event information, and an attribute of each event node comprises the entity information and the event type of the event information (paragraphs [0097]-[0099] A plurality of these, such as all possible two-node subgraphs, or a subset of possible two-node subgraphs of the relational graph may be extracted. In certain embodiments, a plurality of subgraphs of different orders are extracted, and after a set of subgraphs is extracted, each extracted subgraph is indexed and saved in a subgraph feature vocabulary; [0111], subgraphs may be extracted from a database that stores the first relational graph. The number of subgraphs obtained may include p subgraphs. In one embodiment, for example, a plurality of I-node subgraphs (e.g., all of the I-node subgraphs in the first relational graph) and a plurality of 2-node subgraphs (e.g., all of the 2-node subgraphs in the relational graph) may be obtained from the first relational graph. Each obtained subgraph may be indexed (Examiner interprets indexed as identifier), for example in a database; [0122] and [0133].).
It would have been obvious to one of ordinary skill in the art before the effective filing of
the claimed invention to modify the combination system of Carbune, Clark, Shaer, Mithal and Pahud to add subgraph extraction to the combination system of Carbune, Clark, Shaer, Mithal and Pahud, as taught by Choe, above. The modification would have been obvious because one of ordinary skill would be motivated to have extracted subgraphs from each relational graph and dimension reduction may be performed on the subgraphs to reduce the complexity of the search that resources need to perform the search, as suggested by Choe, ([0119]).
Claims 3-4 and 12-13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Carbune et al. (US 2022/0138591 A1, hereinafter referred to as Carbune), in view of Clark et al. (US 2017/0161311 A1, hereinafter referred to as Clark), and further in view of Shaer (US 2002/0128934 A1, hereinafter referred to as Shaer), and Mithal et al. (US 2013/0144748 A1, hereinafter referred to as Mithal), and Pahud et al. (US 2006/0217979 A1, hereinafter referred to as Pahud), and Choe et al. (US 2014/0324864 A1, hereinafter referred to as Choe)., and Kumar et al. (“Extracting large-scale knowledge bases from the web∗,” hereinafter referred to as Kumar).
As to claim 3, which incorporates the rejection of claim 2, Choe, in combination with Carbune, Clark, Shaer, Mithal and Pahud, teaches wherein extracting the subgraph from the event knowledge graph comprises:
extracting a candidate subgraph from the event knowledge graph, the candidate subgraph comprising event nodes in an association relation (paragraphs [0073] …
FIG. 2 shows an exemplary graphical representation of a scene (e.g., including a loading event); [0097]- [0099] In the example of FIG. 4C, each two-node subgraph includes two nodes connected with one edge. A plurality of these, such as all possible two-node subgraphs or a subset of possible two-node subgraphs (Examiner interprets candidate subgraph as candidate subgraph) of the relational graph may be extracted. In the example of FIG. 4D, each three-node subgraph includes three nodes connected with three edges. A plurality of these, such as all possible three-node subgraphs, or a subset of possible three-node subgraphs of the relational graph may be extracted. Also, not all three-node graphs need to include three edges. Further, a subgraph can include only a single edge, or a node and a connected edge without additional elements. In general, groups of subgraphs having the same number of nodes may be referred to as n-node subgraphs).
However, Carbune, Clark, Shaer, Mithal, Pahud and Choe fail to explicitly teach:
extracting the subgraph having a single-chain structure from the candidate subgraph when the candidate subgraph comprises an event node having ail outdegree equal to or greater than 2 or an indegree equal to or greater than 2.
Kumar, in combination with Carbune, Clark, Shaer, Mithal, Pahud and Choe, teaches an event node having an outdegree equal to or greater than 2 or an indegree equal to or greater than 2 (page 8, left column, 5th paragraph, we construct a list of nodes with in-degree or out-degree 3, along with their in- or out-neighborhoods; page 8, right column, Example 4, node with indegree ≤ 2, node with in/out-degree ≤ 2, nodes with in/out-degree equal to 3).
It would have been obvious to one of ordinary skill in the art before the effective filing of
the claimed invention to modify the combination system of Carbune, Clark, Shaer, Mithal, Pahud and Choe to add “an event node having an outdegree equal to or greater than 2 or an indegree equal to or greater than 2” to the combination system of Carbune, Clark, Shaer, Mithal, Pahud and Choe, as taught by Kumar above. The modification would have been obvious because one of ordinary skill would be motivated to construct a list of nodes with in-degree or out-degree 3, as suggested by Kumar (page 8, left column, 5th paragraph).
As to claim 4, which incorporates the rejection of claim 2, Choe, in combination with Carbune, Clark, Shaer, Mithal and Pahud, teaches wherein extracting the subgraph from the event knowledge graph comprises:
determining subgraphs to be extracted from the event knowledge graph (paragraphs [0111], subgraphs may be extracted from a database that stores the first relational graph…not all subgraphs of a given order need to be extracted.); and
extracting the subgraph when the number of nodes in the subgraph is equal to or greater than a preset number, and/or a total popularity degree of the event nodes included in the subgraph is equal to or greater than a preset popularity degree (paragraphs [0027], obtaining p subgraphs from the plurality of relational graphs, where p is an integer greater than 1, the p subgraphs forming portions of the relational graphs, at least some of the p subgraphs comprising at least two nodes of the relational graphs and an edge therebetween; [0111] Regardless of which particular subgraphs are extracted, the set of subgraphs obtained can be said to include p subgraphs, p being an integer greater than 1; wherein using the broadest reasonable interpretation, Examiner interprets the nodes of the p subgraphs to teach the limitation).
It would have been obvious to one of ordinary skill in the art before the effective filing of
the claimed invention to modify the combination system of Carbune, Clark, Shaer, Mithal and Pahud to add subgraph extraction to the combination system of Carbune, Clark, Shaer, Mithal and Pahud, as taught by Choe, above. The modification would have been obvious because one of ordinary skill would be motivated to have extracted subgraphs from each relational graph and dimension reduction may be performed on the subgraphs to reduce the complexity of the search that resources need to perform the search, as suggested by Choe, ([0119]).
As to claim 12, which incorporates the rejection of claim 11, Choe, in combination with Carbune, Clark, Shaer, Mithal and Pahud, teaches wherein the processor is further configured to:
extract a candidate subgraph from the event knowledge graph, the candidate subgraph comprising event nodes in an association relation (paragraphs [0073] …
FIG. 2 shows an exemplary graphical representation of a scene (e.g., including a loading event); [0097]-[0099]…In the example of FIG. 4C, each two-node subgraph includes two nodes connected with one edge. A plurality of these, such as all possible two-node subgraphs or a subset of possible two-node subgraphs (Examiner interprets two-node subgraph as candidate subgraph) of the relational graph may be extracted. In the example of FIG. 4D, each three-node subgraph includes three nodes connected with three edges. A plurality of these, such as all possible three-node subgraphs, or a subset of possible three-node subgraphs of the relational graph may be extracted. Also, not all three-node graphs need to include three edges. Further, a subgraph can include only a single edge, or a node and a connected edge without additional elements. In general, groups of subgraphs having the same number of nodes may be referred to as n-node subgraphs.).
However, Carbune, Clark, Shaer, Mithal, Pahud and Choe fail to explicitly teach:
extract the subgraph having a single-chain structure from the candidate subgraph when the candidate subgraph comprises an event node having an outdegree equal to or greater than 2 or an indegree equal to or greater than 2.
Kumar, in combination with Bhageria, Mithal, Pahud, Taycher, Carbune, IKEDA and Choe, teaches an event node having an outdegree equal to or greater than 2 or an indegree equal to or greater than 2 (page 8, left column, 5th paragraph, we construct a list of nodes with in-degree or out-degree 3, along with their in- or out-neighborhoods; page 8, right column, Example 4, node with indegree ≤ 2, node with in/out-degree ≤ 2, nodes with in/out-degree equal to 3).
It would have been obvious to one of ordinary skill in the art before the effective filing of
the claimed invention to modify the combination system of Carbune, Clark, Shaer, Mithal, Pahud and Choe to add “an event node having an outdegree equal to or greater than 2 or an indegree equal to or greater than 2” to the combination system of Carbune, Clark, Shaer, Mithal, Pahud and Choe, as taught by Kumar above. The modification would have been obvious because one of ordinary skill would be motivated to construct a list of nodes with in-degree or out-degree 3, as suggested by Kumar (page 8, left column, 5th paragraph).
As to claim 13, which incorporates the rejection of claim 11, Carbune, Clark, Shaer, Mithal and Pahud fail to explicitly teach:
determine subgraphs to be extracted from the event knowledge graph; and
extract the subgraph when the number of nodes in the subgraph is equal to or greater than a preset number, and/or a total popularity degree of the event nodes included in the subgraph is equal to or greater than a preset popularity degree.
Choe, in combination with Carbune, Clark, Shaer, Mithal and Pahud, teaches wherein the processor is further configured to:
determine subgraphs to be extracted from the event knowledge graph (paragraphs [0111], subgraphs may be extracted from a database that stores the first relational graph, not all subgraphs of a given order need to be extracted); and
extract the subgraph when the number of nodes in the subgraph is equal to or greater than a preset number, and/or a total popularity degree of the event nodes included in the subgraph is equal to or greater than a preset popularity degree.
(paragraphs [0027], obtaining p subgraphs from the plurality of relational graphs, where p is an integer greater than 1, the p subgraphs forming portions of the relational graphs, at least some of the p subgraphs comprising at least two nodes of the relational graphs and an edge therebetween; [0111] Regardless of which particular subgraphs are extracted, the set of subgraphs obtained can be said to include p subgraphs, p being an integer greater than 1; wherein using the broadest reasonable interpretation, Examiner interprets the nodes of the p subgraphs to teach the limitation).
It would have been obvious to one of ordinary skill in the art before the effective filing of
the claimed invention to modify the combination system of Carbune, Clark, Shaer, Mithal and Pahud to add subgraph extraction to the combination system of Carbune, Clark, Shaer, Mithal and Pahud, as taught by Choe, above. The modification would have been obvious because one of ordinary skill would be motivated to have extracted subgraphs from each relational graph and dimension reduction may be performed on the subgraphs to reduce the complexity of the search that resources need to perform the search, as suggested by Choe, ([0119]).
Claims 5 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Carbune et al. (US 2022/0138591 A1, hereinafter referred to as Carbune), in view of Clark et al. (US 2017/0161311 A1, hereinafter referred to as Clark), and further in view of Shaer (US 2002/0128934 A1, hereinafter referred to as Shaer), and Mithal et al. (US 2013/0144748 A1, hereinafter referred to as Mithal), and Pahud et al. (US 2006/0217979 A1, hereinafter referred to as Pahud), and Choe et al. (US 2014/0324864 A1, hereinafter referred to as Choe), Bhageria et al. (US 2019/0354937 A1, hereinafter referred to as Bhageria), and Taycher et al. (US 2019/0258723 A1, hereinafter referred to as Taycher8723).
As to claim 5, which incorporates the rejection of claim 2, Bhageria teaches:
obtaining the pieces of event information in the associated relation, each piece of event information comprising an event title and report content (paragraphs [0002], obtaining, by the one or more processors, one or more prospective themes for a given event (Examiner interprets given event as event type) and a list of participants (Examiner interprets list of participants to include entity information)comprising a portion of the set of users; identifying, by the one or more processors, one or more preferences, in the digital wardrobes of the portion of the set of users, relevant to each of the one or more prospective themes for the given event (Examiner interprets given event as event type); [0042], obtains a list of possible themes for a given event from the event management system 390. The program code 370 additionally obtains an indication of the prospective participants in the event);
recognizing named entities in the event title of each piece of event information to obtain the entity information of the event information (paragraphs [0043]- [0044], Thus, if the list of possible themes includes a "Country Western" (Examiner interprets given "Country Western" as event title) theme for a given event, the program code 370 determines, based on the digital wardrobe of the user, that this user has a strong preference for this theme).
However, Carbune, Clark, Shaer, Mithal, Pahud, Choe and Bhageria fail to explicitly teach:
classifying the report content of each piece of event information to obtain the event type of the event information; and
constructing an event node with the event information, the entity information and the event type of the event information, and
constructing an edge between event nodes based on the association relation between corresponding event information to generate the event knowledge graph.
Taycher8723, in combination with Carbune, Clark, Shaer, Mithal, Pahud, Choe and Bhageria, teaches:
classifying the report content of each piece of event information to obtain the event type of the event information (paragraphs [0023]- [0025] The event detection unit 132 can analyze the text, images, and video associated with the real-time data feed (i.e., report content) in order to identify event classification data such as an event type, classifying the event in one or more precedent sets, an entity name that is associated with the event, or a combination thereof.; event classification unit 134 ); and
constructing an event node with the event information, the entity information and the event type of the event information (paragraph [0024], generating a new node of
the knowledge graph that represents the detected occurrence of the event.); and
constructing an edge between event nodes based on the association relation between corresponding event information to generate the event knowledge graph (paragraphs [0027] The edges of the directed graph are used to establish relationships between two or more respective nodes of the graph; [0036], creating a plurality of graph edges each of which (i) is associated with the "Smartphone" domain node 162 and (ii) references one or more of the respective event nodes 170, 171, 172, 173; [0038, creating a respective graph edge that is associated with the specific "Smartphone Release" event node 170 and references a respective event precedent node 180-1 to 180-n for smartphone releases generally).
It would have been obvious to one of ordinary skill in the art before the effective filing of
the claimed invention to modify the combination system of Carbune, Clark, Shaer, Mithal, Pahud, Choe and Bhageria to add a report content classification, and a constructing of an event node and an edge to the combination system of Carbune, Clark, Shaer, Mithal, Pahud, Choe and Bhageria, as taught by Taycher8723 above. The modification would have been obvious because one of ordinary skill would be motivated to have edges of the directed graph are used to establish relationships between two or more respective nodes of the graph, as suggested by Taycher8723 ([0027]).
As to claim 14, which incorporates the rejection of claim 11, Bhageria teaches wherein the processor is further configured to:
obtain the pieces of event information in the associated relation, each piece of event information comprising an event title and report content (paragraphs [0002], obtaining, by the one or more processors, one or more prospective themes for a given event (Examiner interprets “a given event” as event type) and a list of participants (Examiner interprets “list of participants” to include entity information) comprising a portion of the set of users; identifying, by the one or more processors, one or more preferences, in the digital wardrobes of the portion of the set of users, relevant to each of the one or more prospective themes for the given event (Examiner interprets “a given event” as event type); [0042], obtains a list of possible themes for a given event from the event management system 390. The program code 370 additionally obtains an indication of the prospective participants in the event);
recognize named entities in the event title of each piece of event information to obtain the entity information of the event information (paragraphs [0043]-[0044]…Thus, if the list of possible themes includes a "Country Western" (Examiner interprets "Country Western" as event title) theme for a given event, the program code 370 determines, based on the digital wardrobe of the user, that this user has a strong preference for this theme.)
However, Carbune, Clark, Shaer, Mithal, Pahud, Choe and Bhageria fail to explicitly teach:
Classify the report content of each piece of event information to obtain the event type of the event information; and
constructing an event node with the event information, the entity information and the event type of the event information, and
constructing an edge between event nodes based on the association relation between corresponding event information to generate the event knowledge graph.
Taycher8723, in combination with Carbune, Clark, Shaer, Mithal, Pahud, Choe and Bhageria, teaches:
classifying the report content of each piece of event information to obtain the event type of the event information (paragraphs [0023]- [0025] The event detection unit 132 can analyze the text, images, and video associated with the real-time data feed (Examiner interprets “real-time data feed” as report content) in order to identify event classification data such as an event type, classifying the event in one or more precedent sets, an entity name that is associated with the event, or a combination thereof; event classification unit 134); and
constructing an event node with the event information, the entity information and the event type of the event information (paragraph [0024], generating a new node of
the knowledge graph that represents the detected occurrence of the event.); and
constructing an edge between event nodes based on the association relation between corresponding event information to generate the event knowledge graph (paragraphs [0027] The edges of the directed graph are used to establish relationships between two or more respective nodes of the graph; [0036], creating a plurality of graph edges each of which (i) is associated with the "Smartphone" domain node 162 and (ii) references one or more of the respective event nodes 170, 171, 172, 173; [0038, creating a respective graph edge that is associated with the specific "Smartphone Release" event node 170 and references a respective event precedent node 180-1 to 180-n for smartphone releases generally).
It would have been obvious to one of ordinary skill in the art before the effective filing of
the claimed invention to modify the combination system of Carbune, Clark, Shaer, Mithal, Pahud, Choe and Bhageria to add a report content classification, and a constructing of an event node and an edge to the combination system of Carbune, Clark, Shaer, Mithal, Pahud, Choe and Bhageria, as taught by Taycher873 above. The modification would have been obvious because one of ordinary skill would be motivated to have edges of the directed graph are used to establish relationships between two or more respective nodes of the graph, as suggested by Taycher8723 ([0027]).
Claims 7 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Carbune et al. (US 2022/0138591 A1, hereinafter referred to as Carbune), in view of Clark et al. (US 2017/0161311 A1, hereinafter referred to as Clark), and further in view of Shaer (US 2002/0128934 A1, hereinafter referred to as Shaer), and Mithal et al. (US 2013/0144748 A1, hereinafter referred to as Mithal), and Pahud et al. (US 2006/0217979 A1, hereinafter referred to as Pahud), and Briancon et al. (US 2020/0126126 A1, hereinafter referred to as Briancon).
As to claim 7, which incorporates the rejection of claim 1, Mithal teaches wherein obtaining the target event information having representative attributes from the pieces of event information.
However, Carbune, Clark, Shaer, Mithal and Pahud fail to explicitly teach:
sorting the pieces of event information based on an occurrence time sequence of the pieces of event information; and
selecting a first piece or a last piece from pieces of sorted event information as the target event information.
Briancon, in combination with Carbune, Clark, Shaer, Mithal and Pahud, teaches:
sorting the pieces of event information based on an occurrence time sequence of the pieces of event information (paragraphs [0056]-[0058] In some embodiments, the
time-series of events may include a plurality of time-series sequences of events, where each time-series sequences of events is an ordered sequence of two or more events having same or similar event types. In some embodiments, the time-series of events may include a plurality of time-series sequences of events, where each time-series sequences of events is an ordered sequence of two or more events having
one or more specified event types.); and
selecting a first piece or a last piece from pieces of sorted event information as the target event information (paragraphs [0058]- [0059] In some embodiments, event types may be stored in an ontology of event types that describes the interrelatedness,
similarity, or both interrelatedness and similarity of different event types represented in the time-series of events. Some of the events may include a question types of
events presented to an actor-entity along with the response obtained from the actor-entity. In some embodiments, a question event may be an interactive user interface element for which a response within the user interface element is collected, which may be a selection or other user input.)
It would have been obvious to one of ordinary skill in the art before the effective filing of
the claimed invention to modify the combination system of Carbune, Clark, Shaer, Mithal and Pahud to add a time sequence of events to the combination system of Carbune, Clark, Shaer, Mithal and Pahud, as taught by Briancon above. The modification would have been obvious because one of ordinary skill would be motivated to optimize an objective function that indicates an accuracy of the machine-learning model in predicting subsequent events in the time-series given prior events in the time-series and given attributes of subject entities among the population, as suggested by Briancon ([0007]).
As to claim 16, which incorporates the rejection of claim 1, Carbune, Clark, Shaer, Mithal and Pahud fail to explicitly teach wherein the processor is further configured to:
sort the pieces of event information based on an occurrence time sequence of the pieces of event information; and
select a first piece or a last piece from pieces of sorted event information as the target event information.
Briancon, in combination with Carbune, Clark, Shaer, Mithal and Pahud, teaches wherein the processor is further configured to:
sort the pieces of event information based on an occurrence time sequence of the pieces of event information (paragraphs [0056]-[0058] In some embodiments, the
time-series of events may include a plurality of time-series sequences of events, where each time-series sequences of events is an ordered sequence of two or more events having same or similar event types. In some embodiments, the time-series of events may include a plurality of time-series sequences of events, where each time-series sequences of events is an ordered sequence of two or more events having
one or more specified event types.); and
select a first piece or a last piece from pieces of sorted event information as the target event information (paragraphs [0058]-[0059] In some embodiments, event types may be stored in an ontology of event types that describes the interrelatedness,
similarity, or both interrelatedness and similarity of different event types represented in the time-series of events. Some of the events may include a question types of
events presented to an actor-entity along with the response obtained from the actor-entity. In some embodiments, a question event may be an interactive user interface element for which a response within the user interface element is collected, which may be a selection or other user input.).
It would have been obvious to one of ordinary skill in the art before the effective filing of
the claimed invention to modify the combination system of Carbune, Clark, Shaer, Mithal and Pahud to add a time sequence of events to the combination system of Carbune, Clark, Shaer, Mithal and Pahud, as taught by Briancon above. The modification would have been obvious because one of ordinary skill would be motivated to optimize an objective function that indicates an accuracy of the machine-learning model in predicting subsequent events in the time-series given prior events in the time-series and given attributes of subject entities among the population, as suggested by Briancon ([0007]).
Claims 8 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Carbune et al. (US 2022/0138591 A1, hereinafter referred to as Carbune), in view of Clark et al. (US 2017/0161311 A1, hereinafter referred to as Clark), and further in view of Shaer (US 2002/0128934 A1, hereinafter referred to as Shaer), and Mithal et al. (US 2013/0144748 A1, hereinafter referred to as Mithal), and Pahud et al. (US 2006/0217979 A1, hereinafter referred to as Pahud), and Briancon et al. (US 2020/0126126 A1, hereinafter referred to as Briancon), and ADACHI et al. (US 2016/0111010 A1, hereinafter referred to as ADACHI).
As to claim 8, which incorporates the rejection of claim 7, Carbune, Clark, Shaer, Mithal, Pahud and Briancon fail to explicitly teach:
calculating a similarity between every two pieces of event information; and
removing one of two pieces of event information, when the similarity between the two pieces of event information exceeds a preset similarity threshold.
However, ADACHI, in combination with Carbune, Clark, Shaer, Mithal, Pahud and Briancon, teaches:
calculating a similarity between every two pieces of event information (paragraphs [0035] and [0045]-[0046] The event similarity information 126 is information obtained by associating the question whose similarity is calculated by the question candidate extraction unit 112 with the calculated similarity; [0088]-[0089] and [0097], calculates the similarity based on the sequence of the event 121c associated with the question and the sequence of the operation history identified in Step S12); and
removing one of two pieces of event information, when the similarity between the two pieces of event information exceeds a preset similarity threshold (paragraphs [0102]-[0104] Note that, whose similarity is not 0% exists in the event similarity information 126. Note that, the question candidate extraction unit 112 may determine that there is a similar event when the event similarity information 126 includes a question having a similarity that exceeds a threshold value stored in an area (not shown) of the storage unit 120. Specifically, the question candidate extraction unit 112 extracts (i.e., removes) a predetermined number of records from among the records included in the event similarity information 126 in descending order of the similarity, and notifies the output unit 114 of the extracted records as the question candidates.).
It would have been obvious to one of ordinary skill in the art before the effective filing of
the claimed invention to modify the combination system of Carbune, Clark, Shaer, Mithal, Pahud and Briancon, to add a similarity threshold to the combination system of Carbune, Clark, Shaer, Mithal, Pahud and Briancon, as taught by ADACHI above. The modification would have been obvious because one of ordinary skill would be motivated to eliminate time and labor to make a search for an appropriate question with efficiency, as suggested by ADACHI (0108]).
As to claim 17, which incorporates the rejection of claim 16, Carbune, Clark, Shaer, Mithal, Pahud and Briancon fail to explicitly teach wherein the processor is further configured to:
calculate a similarity between every two pieces of event information; and
removing one of two pieces of event information, when the similarity between the two pieces of event information exceeds a preset similarity threshold.
However, ADACHI, in combination with Carbune, Clark, Shaer, Mithal, Pahud and Briancon, teach wherein the processor is further configured to:
calculate a similarity between every two pieces of event information (paragraphs [0035] and [0045]-[0046] The event similarity information 126 is information obtained by associating the question whose similarity is calculated by the question candidate extraction unit 112 with the calculated similarity; [0088]-[0089] and [0097], calculates the similarity based on the sequence of the event 121c associated with the question and the sequence of the operation history identified in Step S12); and
remove one of two pieces of event information, when the similarity between the two pieces of event information exceeds a preset similarity threshold (paragraphs [0102]-[0104] Note that, whose similarity is not 0% exists in the event similarity information 126. Note that, the question candidate extraction unit 112 may determine that there is a similar event when the event similarity information 126 includes a question having a similarity that exceeds a threshold value stored in an area (not shown) of the storage unit 120. Specifically, the question candidate extraction unit 112 extracts (Examiner interprets “extracts” as removes), a predetermined number of records from among the records included in the event similarity information 126 in descending order of the similarity, and notifies the output unit 114 of the extracted records as the question candidates.)
It would have been obvious to one of ordinary skill in the art before the effective filing of
the claimed invention to modify the combination system of Carbune, Clark, Shaer, Mithal, Pahud and Briancon to add a similarity threshold to the combination system of Carbune, Clark, Shaer, Mithal, Pahud and Briancon, as taught by ADACHI above. The modification would have been obvious because one of ordinary skill would be motivated to eliminate time and labor to make a search for an appropriate question with efficiency, as suggested by ADACHI (0108]).
Claims 9 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Carbune et al. (US 2022/0138591 A1, hereinafter referred to as Carbune), in view of Clark et al. (US 2017/0161311 A1, hereinafter referred to as Clark), and further in view of Shaer (US 2002/0128934 A1, hereinafter referred to as Shaer), and Mithal et al. (US 2013/0144748 A1, hereinafter referred to as Mithal), and Pahud et al. (US 2006/0217979 A1, hereinafter referred to as Pahud), and KANG (US 2017/0154077 A1, hereinafter referred to as KANG), and PALI GA et al. (US 2021/0118269 A1, hereinafter referred to as PALIGA).
As to claim 9, which incorporates the rejection of claim 1, Carbune, Clark, Shaer, Mithal and Pahud fail to explicitly teach:
counting the number of pieces of different entity information and the number of different event types of the pieces of event information;
determining a first theme modifier word for each piece of different entity information when the number of pieces of the different entity information exceeds a preset threshold;
determining a second theme modifier word for each different event type, when the number of different event types exceeds the preset threshold; and
wherein adding the entity information and the event type of the target event information into the theme template to generate the theme of the pieces of event information comprises:
adding the entity information, the event type, the first theme modifier word and the second theme modifier word of the target event information into the theme template to generate the theme of the pieces of event information.
KANG, in combination with Carbune, Clark, Shaer, Mithal and Pahud, teaches:
counting the number of pieces of different entity information and the number of different event types of the pieces of event information (paragraphs [0053] -- [0054], identify (Examiner interprets identify as counting) the general feeling, attitude or opinion that the author of a section of unstructured text is expressing towards a situation or event);
determining a first theme modifier word for each piece of different entity information when the number of pieces of the different entity information exceeds a preset threshold (paragraph [0009], performing binary group extraction on each comment corresponding to a current to-be-processed object, and combining the extracted binary group into a first set, wherein the binary group comprises subject words and modifiers (Examiner interprets modifiers to include a first theme modifier word); determining words of which term frequency-inverse document frequency (TF-IDF) is greater than a first preset threshold value in each comment);
determining a second theme modifier word for each different event type, when the number of different event types exceeds the preset threshold (paragraph [0009], performing binary group extraction on each comment corresponding to a current to-be-processed object, and combining the extracted binary group into a first set, wherein the binary group comprises subject words and modifiers (Examiner interprets modifiers to include a second theme modifier word); determining words of which term frequency-inverse document frequency (TF-IDF) is greater than a first preset threshold value in each comment, and combining the determined words into a second set; processing the first set and the second set according to a first preset rule to generate a third set; wherein using the broadest reasonable interpretation, Examiner in the interprets the “combining the determined words into a second set” teach the limitation).
However, Carbune, Clark, Shaer, Mithal, Pahud and KANG fail to explicitly teach:
wherein adding the entity information and the event type of the target event information into the theme template to generate the theme of the pieces of event information comprises:
adding the entity information, the event type, the first theme modifier word and the second theme modifier word of the target event information into the theme template to generate the theme of the pieces of event information.
PALIGA, in combination with Carbune, Clark, Shaer, Mithal, Pahud and KANG, teaches:
wherein adding the entity information and the event type of the target event information into the theme template to generate the theme of the pieces of event information comprises:
adding the entity information, the event type, the first theme modifier word and the second theme modifier word of the target event information into the theme template to generate the theme of the pieces of event information (paragraphs [01887].[0188],a customizable HTML theme, and the like, to customize their online store 138. Merchants may customize the look and feel of their website through a theme system, such as where merchants can select and change the look and feel of their online store 138 by changing their theme while having the same underlying product and business data shown within the online store's product hierarchy. Themes may be further customized through a theme editor, a design interface that enables users to customize their website's design with flexibility. Themes may also be customized using theme-specific settings that change aspects, such as specific colors, fonts, and pre-built layout schemes).
It would have been obvious to one of ordinary skill in the art before the effective filing of
the claimed invention to modify the combination system of Carbune, Clark, Shaer, Mithal, Pahud and KANG to add theme modifiers to the combination system of Carbune, Clark, Shaer, Mithal, Pahud and KANG, as taught by PALIGA above. The modification would have been obvious because one of ordinary skill would be motivated to customize themes through a theme editor, a design interface that enables users to customize their website's design with flexibility, as suggested by PALIGA ([0188]).
As to claim 18, which incorporates the rejection of claim 10, Carbune, Clark, Shaer, Mithal, Pahud and KANG fail to explicitly teach:
count the number of pieces of different entity information and the number of different event types of the pieces of event information;
determine a first theme modifier word for each piece of different entity information when the number of pieces of the different entity information exceeds a preset threshold;
determine a second theme modifier word for each different event type, when the number of different event types exceeds the preset threshold; and
adding the entity information, the event type, the first theme modifier word and the second theme modifier word of the target event information into the theme template to generate the theme of the pieces of event information.
KANG, in combination with Carbune, Clark, Shaer, Mithal, Pahud and KANG, teaches:
count the number of pieces of different entity information and the number of different event types of the pieces of event information (paragraphs [0053] -- [0054], identify (Examiner interprets identify as counting) the general feeling, attitude or opinion that the author of a section of unstructured text is expressing towards a situation or event);
determine a first theme modifier word for each piece of different entity information when the number of pieces of the different entity information exceeds a preset threshold (paragraph [0009], performing binary group extraction on each comment corresponding to a current to-be-processed object, and combining the extracted binary group into a first set, wherein the binary group comprises subject words and modifiers (Examiner interprets modifiers to include a first theme modifier word); determining words of which term frequency-inverse document frequency (TF-IDF) is greater than a first preset threshold value in each comment);
determine a second theme modifier word for each different event type, when the number of different event types exceeds the preset threshold (paragraph [0009], performing binary group extraction on each comment corresponding to a current to-be-processed object, and combining the extracted binary group into a first set, wherein the binary group comprises subject words and modifiers (Examiner interprets modifiers to include a second theme modifier word); determining words of which term frequency-inverse document frequency (TF-IDF) is greater than a first preset threshold value in each comment, and combining the determined words into a second set; processing the first set and the second set according to a first preset rule to generate a third set; wherein using the broadest reasonable interpretation, Examiner in the interprets the “combining the determined words into a second set” teach the limitation).
However, Carbune, Clark, Shaer, Mithal, Pahud and KANG fail to explicitly teach:
add the entity information, the event type, the first theme modifier word and the second theme modifier word of the target event information into the theme template to generate the theme of the pieces of event information.
PALIGA, in combination with Carbune, Clark, Shaer, Mithal, Pahud and KANG, teaches:
add the entity information, the event type, the first theme modifier word and the second theme modifier word of the target event information into the theme template to generate the theme of the pieces of event information (paragraphs [01887].[0188], a customizable HTML theme, and the like, to customize their online store 138. Merchants may customize the look and feel of their website through a theme system, such as where merchants can select and change the look and feel of their online store 138 by changing their theme while having the same underlying product and business data shown within the online store's product hierarchy. Themes may be further customized through a theme editor, a design interface that enables users to customize their website's design with flexibility. Themes may also be customized using theme-specific settings that change aspects, such as specific colors, fonts, and pre-built layout schemes).
It would have been obvious to one of ordinary skill in the art before the effective filing of
the claimed invention to modify the combination system of Carbune, Clark, Shaer, Mithal, Pahud and KANG to add theme modifiers to the combination system of Carbune, Clark, Shaer, Mithal, Pahud and KANG, as taught by PALIGA above. The modification would have been obvious because one of ordinary skill would be motivated to customize themes through a theme editor, a design interface that enables users to customize their website's design with flexibility, as suggested by PALIGA ([0188]).
Response to Applicant’s arguments
Applicant's arguments on file on 02/12/2026 with respect to claims 1-5, 7-14 and 16-20 have been considered are not persuasive for moot in view of new ground(s) of rejection.
Claims Rejections - 35 U.S.C. § 101
Claims 1-5, 7-14 and 16-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Argument (page 10)
Step 2A Prong 1 - The Claims Do Not Recite A Judicial Exception
The Office Action alleged that the selecting step, the adding step and the generation
step are performed in the human mind.
Applicant appears to assert that the limitations of amended claim 1 are not "mental process". Therefore, Applicant disagrees that the claims are "directed to" an abstract idea under Step 2A, Prong 1 of the 2019 Revised Patent Subject Matter Eligibility Guidance.
Examiner response
Examiner respectfully disagrees. The claim does recite a mental process when they contain limitations that can practically be performed in the human mind, including for example, observations, evaluations, judgments, and opinions. (MPEP 2106.04(a)(2)).
The claimed “selecting” is an observation or evaluation based a theme template matching the event type of the target event information from a theme template collection. This type of observation or evaluation is an act that can be practically performed in the human mind, similar to the mental thought processes that occur when a person selects a theme or subject for a birthday event from a birthday theme template. Such mental observations or evaluations fall within the “mental processes” grouping of abstract idea set forth in the 2019 PEG. 2019 PEG Section I, 84 Fed. Reg. at 52.
Examiner interpreted this limitation as an observation. See MPEP 2106.04(a), particularly MPEP 2106.04(a)(2)(III)(C).
The claimed “adding” is an observation or evaluation based on the entity information and the event type of the target event information into the theme template. This type of observation or evaluation is an act that can be practically performed in the human mind, similar to the mental thought processes that occur when a person adds a profile information and the interest type of the event information into the theme template. Such mental observations or evaluations fall within the “mental processes” grouping of abstract idea set forth in the 2019 PEG. 2019 PEG Section I, 84 Fed. Reg. at 52.
Examiner interpreted this limitation as an observation. See MPEP 2106.04(a), particularly MPEP 2106.04(a)(2)(III)(C).
The claimed “generate” is an observation or evaluation based on a theme of the pieces of event information. This type of observation or evaluation is an act that can be practically performed in the human mind, similar to the mental thought processes that occur when a person wrote the lyrics of an opening for a television show. Such mental observations or evaluations fall within the “mental processes” grouping of abstract idea set forth in the 2019 PEG. 2019 PEG Section I, 84 Fed. Reg. at 52.
Examiner interpreted this limitation as an observation. See MPEP 2106.04(a), particularly MPEP 2106.04(a)(2)(III)(C).
The claimed “generating” is an observation or evaluation based on the theme of the pieces of event information by taking the entity information of the target event information as a subject of the segment of text and by taking the event type of the target event information as a predicate of the e template segment of text. This type of observation or evaluation is an act that can be practically performed in the human mind, similar to the mental thought processes that occur when a person wrote the lyrics of an opening for a music concert. Such mental observations or evaluations fall within the “mental processes” grouping of abstract idea set forth in the 2019 PEG. 2019 PEG Section I, 84 Fed. Reg. at 52.
Examiner interpreted this limitation as an observation. See MPEP 2106.04(a), particularly MPEP 2106.04(a)(2)(III)(C).
The newly added claim features do not improve the functionality of a computer or any technology.
Therefore, claims are "directed to" an abstract idea under Step 2A, Prong 1 of the 2019 Revised Patent Subject Matter Eligibility Guidance.
Argument (pages 10-11)
Under Step 2A, Prong 2 - Even if They Recite a Judicial Exception, the Claims Are Directed to a Practical Application of that Exception
The method of amended claim 1 is to be integrated into a field of knowledge graph
technology, specifically to extracting structured data from a knowledge graph and generating structured text. In detail, a plurality of pieces of event information is obtained from the event knowledge graph, the event knowledge graph includes the entity information and event type as the event nodes and the associated relation as edge information between event nodes. The target event information is determined from the plurality of pieces of event information, and a matching theme template is determined from the theme template collection. The theme template is a segment of text
having positions to be filled. The entity information is added as the subject of the segment of text and the event type is added as the predicate of the segment text.
Examiner response
Examiner respectfully disagrees. For Step 2A, Prong 2, the claim recites additional elements: memory, apparatus, deep learning, “obtaining a plurality of pieces of event information in an associated relation,” “obtaining entity information and an event type of each piece of event information” and “obtaining target event information having representative attributes from the pieces of event information.”
The "apparatus" is one of the four categories of patentable subject matter (along with process, machine, and composition of matter) and is used to describe a device or a system. MPEP 2106.05(f)
The recited “deep learning (i.e. as a type of machine learning that uses algorithms that are structured in layers)” amounts to mere instructions to apply an abstract idea under MPEP 2106.05 (f).
The “obtaining a plurality of pieces of event information in an associated relation” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The “obtaining entity information and an event type of each piece of event information” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The “obtaining target event information having representative attributes from the pieces of event information” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The “memory” is a generic computer component that amount to mere instructions to apply the abstract idea. See MPEP 2106.05(f).
The “display” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
Argument (page 11)
Under Step 2B - Even if They Are Not Directed to a Practical Application of that Exception, the Claims Are Significantly More Than the Abstract Idea Itself
With the amended claim 1, the event knowledge graph is obtained and stored in the
local memory, which may save storage space. In addition, extracting structured data directly from the knowledge graph may improve data extraction speed and using the theme template to generate the theme may facilitate to recognize and process the structured text, thereby increasing the speed of text generation. Thus, amended claim 1 is significantly more than the abstract idea itself.
In conclusion, the claimed subject matter is patentable. Withdrawal of the rejection is
respectfully requested.
Examiner response
Examiner respectfully disagrees. The additional elements of “memory,” “apparatus “and “deep learning” do not amount to significantly more for the reasons set forth in step 2A above.
Under the Subject Matter Eligibility (SME), a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be reevaluated in Step 2B (see rejection above).
As described in MPEP § 2106.05(f), additional elements (for example an apparatus) that invoke computers or other machinery merely as a tool to perform an existing process will generally not amount to significantly more than a judicial exception. See, e.g., Versata Development Group v. SAP America, 793 F.3d 1306, 1335, 115 USPQ2d 1681, 1702 (Fed. Cir. 2015) (explaining that in order for a machine to add significantly more, it must "play a significant part in permitting the claimed method to be performed, rather than function solely as an obvious mechanism for permitting a solution to be achieved more quickly".)
The newly added claim features do not improve the functionality of a computer or any technology (see rejection above).
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of “memory,” “apparatus” and “deep learning” to perform the claim steps amount to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim is not patent eligible.
Claims Rejections - 35 U.S.C. § 103
Applicant’s arguments are moot in view of new ground(s) of rejection: Carbune et al. (US 2022/0138591 A1), Clark et al. (US 2017/0161311 A1, hereinafter referred to as Clark), and Shaer (US 2002/0128934 A1).
Conclusion
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/ABABACAR SECK/Examiner, Art Unit 2147
/VIKER A LAMARDO/Supervisory Patent Examiner, Art Unit 2147
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