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 .
Response to Amendment
Acknowledgment is made of applicant’s amendment filed on 22 June 2026.
Claims 1, 3-17 and 19-20 are presented for examination.
Claims 1, 3-11, 17, 19-20 are rejected.
Claims 1, 3, 4, 5, 7, 8, 9, 10, 11, 17, 19 and 20 are amended.
Claims 2, 18 are canceled.
Claims 12-16 are withdrawn.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. CN2023115594193.6, filed on 21 November 2023.
Response to Argument
Applicant’s arguments for 35 U.S.C. 101 rejection filed in the amendment filed on 22 June 2026, have been fully considered but they are not deemed persuasive.
Applicant’s arguments for 35 U.S.C. 102/103 rejection filed in the amendment filed on 22 June 2026, have been considered but are moot because the arguments do not apply to any of the references being used in the current rejection.
Applicant argued that “Applicant respectfully traverses the rejection.
As amended, independent claim 1 no longer merely recites receiving search information and generating display information in general. Instead, claim 1 now requires at least the following coordinated technical features: (i) obtaining object search information, wherein the object search information is information described in an unstructured language; (ii) sending intention analysis information to a first model, wherein the first model is a model having a natural language processing function; (iii) receiving intention information sent by the first model, wherein the intention information is determined based on the object search information, and the intention information is implemented in a form of a Key-Value pair.
These features are not directed to a mental process that can be practically performed in the human mind. The claimed process uses a model having a natural language processing function to process unstructured-language object search information and to output machine-usable intention information in the form of a Key-Value pair. A human mind may understand natural language in a general sense, but the claimed process is a specific computer-implemented data processing procedure rather than an observation, evaluation, judgment, or opinion that can be performed mentally.
Further, even if claim 1 were considered to recite an abstract idea at some level of generality, amended claim 1 integrates any such idea into a practical application. In particular, the claim converts unstructured-language object search information into structured intention information in the form of a Key-Value pair. The claimed process therefore improves how a computer system processes unstructured object search information and determines object information to be displayed, rather than merely presenting results of a mental evaluation.”
Examiner respectfully disagrees.
MPEP 2106.04(a)(2)(III)(C), “A Claim That Requires a Computer May Still Recite a Mental Process…
1. Performing a mental process on a generic computer…
2. Performing a mental process in a computer environment…
3. Using a computer as a tool to perform a mental process…”
Therefore, even if the argued claim limitations “(i) obtaining object search information, wherein the object search information is information described in an unstructured language; (ii) sending intention analysis information to a first model, wherein the first model is a model having a natural language processing function; (iii) receiving intention information sent by the first model, wherein the intention information is determined based on the object search information, and the intention information is implemented in a form of a Key-Value pair” are performed on a computer, the claims recites a mental process.
Further, the claim is broad, other than using “first model” as tool, nothing in the claim element precludes the step from practically being performed in the mind. A person can convert unstructured-language object search information into structured intention information in the form of a Key-Value pair in his mind.
Applicant argued that “…Further, even if claim 1 were considered to recite an abstract idea at some level of generality, amended claim 1 integrates any such idea into a practical application. In particular, the claim converts unstructured-language object search information into structured intention information in the form of a Key-Value pair. The claimed process therefore improves how a computer system processes unstructured object search information and determines object information to be displayed, rather than merely presenting results of a mental evaluation.”
Examiner respectfully disagrees. Converting unstructured natural language data into structured format such as “key-value pairs” is a well-established concept in computer science. For example mapping unstructured text into key-value attributes (e.g., transforming "find a cheap Italian restaurant in Boston" into {"cuisine": "Italian", "location": "Boston", "price": "low"}) relied heavily on three main paradigms:
Rule-Based and Grammar Systems: Utilizing hand-crafted context-free grammars (CFGs), regular expressions, and semantic lexicons to parse queries.
Hidden Markov Models (HMMs) and Conditional Random Fields (CRFs): Treating the extraction as a sequence labeling task where tokens in the unstructured query are tagged with specific attribute keys.
Classification and Keyword Mapping: Breaking down the query into tokens and using statistical classifiers (like Naive Bayes or SVMs) to map extracted keywords to predefined database schema slots.
Further, the structure of key-value pair is abstract idea. MPEP 2106.05(a)(I), “vii. Providing historical usage information to users while they are inputting data, in order to improve the quality and organization of information added to a database, because “an improvement to the information stored by a database is not equivalent to an improvement in the database’s functionality…”
MPEP 2106.05(f)(1), “In addition to the abstract idea, the claims also recited the additional element of modifying the underlying XML document in response to modifications made in the dynamic document. 850 F.3d at 1342; 121 USPQ2d at 1947-48. Although the claims purported to modify the underlying XML document in response to modifications made in the dynamic document, nothing in the claims indicated what specific steps were undertaken other than merely using the abstract idea in the context of XML documents. The court thus held the claims ineligible, because the additional limitations provided only a result-oriented solution and lacked details as to how the computer performed the modifications, which was equivalent to the words “apply it”. 850 F.3d at 1341-42; 121 USPQ2d at 1947-48 (citing Electric Power Group., 830 F.3d at 1356, 1356, USPQ2d at 1743-44 (cautioning against claims “so result focused, so functional, as to effectively cover any solution to an identified problem”)).”
The claim merely recites,
obtaining object search information, wherein the object search information is information described in an unstructured language;
sending intention analysis information to a first model, wherein the intention analysis information is generated based on the object search information, and the first model is a model having a natural language processing function;
receiving intention information sent by the first model, wherein the intention information is determined based on the object search information, and the intention information is implemented in a form of a Key-Value pair; and
The claim does not clearly recite “convert” step that “converts unstructured-language object search information into structured intention information in the form of a Key-Value pair” which was equivalent to the words “apply it.”
For the above reasons, the rejections are maintained.
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.
Claim 1-11 and 17-20 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1 recites, “A data processing method, comprising:
obtaining object search information, wherein the object search information is information described in an unstructured language;
sending intention analysis information to a first model, wherein the intention analysis information is generated based on the object search information, and the first model is a model having a natural language processing function;
receiving intention information sent by the first model, wherein the intention information is determined based on the object search information, and the intention information is implemented in a form of a Key-Value pair; and
generating object display information, wherein the object display information is determined based on information of at least one object, the at least one object is determined based on the intention information, and each object among the at least one object is matched with the object search information;
wherein after the intention information is received and before the object display information is sent, the method further comprises:
determining condition information based on the intention information; and
determining the at least one object based on the condition information, wherein information of each object among the at least one object is matched with the condition information.
(Step 1) The claim recites “A data processing method, comprising…” as drafted, the claimed method is a process, which is a statutory category of invention.
(Step 2A-Prong One) The limitations of “generating object display information, wherein the object display information is determined based on information of at least one object, the at least one object is determined based on the intention information, and each object among the at least one object is matched with the object search information;” “determining condition information based on the intention information;” and “determining the at least one object based on the condition information, wherein information of each object among the at least one object is matched with the condition information.” 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, other than reciting “model,” nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “model” language, “generating” and “determining” in the context of this claim encompasses the user manually “generating object display information, wherein the object display information is determined based on information of at least one object, the at least one object is determined based on the intention information, and each object among the at least one object is matched with the object search information;” “determining condition information based on the intention information;” and “determining the at least one object based on the condition information, wherein information of each object among the at least one object is matched with the condition information” in his mind.
If claim limitations, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas.
(Step 2A-Prong Two) This judicial exception is not integrated into a practical application.
In particular, the claim recites additional elements – using “model” to perform the “obtaining,” “sending,” “receiving,” “generating,” “determining” and “determining” steps. The “model” in these steps are recited at a high-level of generality such that they amount no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Further, the claim recites additional element – “obtaining object search information, wherein the object search information is information described in an unstructured language;”
“sending intention analysis information to a first model, wherein the intention analysis information is generated based on the object search information, and the first model is a model having a natural language processing function;”
“receiving intention information sent by the first model, wherein the intention information is determined based on the object search information, and the intention information is implemented in a form of a Key-Value pair;” which is Mere data gathering or Selecting a particular data source or type of data to be manipulate and is in form of insignificant extra-solution activity (MPEP: 2106.05 (g), “iv. Obtaining information about transactions using the Internet to verify credit card transactions, CyberSource v. Retail Decisions, Inc.,” “v. Consulting and updating an activity log, Ultramercial.” “iii. Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, Electric Power Group, LLC v. Alstom S.A” and “iv. Requiring a request from a user to view an advertisement and restricting public access, Ultramercial…”).
(Step 2B) 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 using “model” to perform “obtaining,” “sending,” “receiving,” “generating,” “determining” and “determining” steps amounts to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. The claim is not patent eligible.
Further, the other additional limitations “obtaining,” “sending,” “receiving” and “generating” are not sufficient to amount to significantly more than the judicial exception because “obtaining,” “sending,” “receiving” and “generating” only add well-understood, routine and conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception. For example, MPEP 2106.05(d)(II), “i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec… ” “ii. Performing repetitive calculations, Flook, 437 U.S. at 594, 198 USPQ2d at 199 (recomputing or readjusting alarm limit values)” “v. Analyzing DNA to provide sequence information or detect allelic variants, Genetic Techs,” and “iii. Electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225, 110 USPQ2d 1984 (2014) (creating and maintaining "shadow accounts"); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log).”
Thus, the limitation does not amount to significantly more. Even when considered in combination, these additional elements represent mere instructions to apply an exception and insignificant extra-solution activity, which do not provide an inventive concept. The claim is not patent eligible.
For claim 3, it recites “The method according to claim 1, wherein the intention information comprises at least one piece of first-type intention information, and the condition information comprises first-type condition information, wherein the first-type intention information is used to describe the first-type condition information; the method further comprises:
determining the at least one object from an object information database, and the determining the at least one object from the object information database comprises:
determining a first candidate object set from an original object set based on the first- type condition information, wherein information of an object in the first candidate object set is matched with the first-type condition information; and
determining the at least one object from the first candidate object set.”
(Step 2A-Prong One) The limitations of “determining the at least one object from an object information database, and the determining the at least one object from the object information database comprises: determining a first candidate object set from an original object set based on the first- type condition information, wherein information of an object in the first candidate object set is matched with the first-type condition information; and determining the at least one object from the first candidate object set,” 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, other than reciting “model,” nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “model” language, “determining,” “determining” and “determining” in the context of this claim encompasses the user manually “determining the at least one object from an object information database, and the determining the at least one object from the object information database comprises: determining a first candidate object set from an original object set based on the first- type condition information, wherein information of an object in the first candidate object set is matched with the first-type condition information; and determining the at least one object from the first candidate object set” in his mind.
If claim limitations, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas.
Additionally, claim limitation “the intention information comprises at least one piece of first-type intention information, and the condition information comprises first-type condition information, wherein the first-type intention information is used to describe the first-type condition information; the method further comprises:” which is merely data (e.g. contents) and does not meet any of the categories (MPEP: 2106.03, “Thus, the Federal Circuit has held that a product claim to an intangible collection of information, even if created by human effort, does not fall within any statutory category. Digitech, 758 F.3d at 1350, 111 USPQ2d at 1720 (claimed "device profile" comprising two sets of data did not meet any of the categories because it was neither a process nor a tangible product).”).
(Step 2A-Prong Two) and (Step 2B)
No additional elements are provided in the claim, therefore there is still no practical application and the claim does not provide significantly more as per claim 1 analysis.
For claim 4, it recites “The method according to claim 3, wherein the intention information further comprises at least one piece of second-type intention information, and the condition information further comprises second-type condition information, wherein the second-type condition information is obtained by vectorizing the at least one piece of second-type intention information; and
determining the at least one object from the first candidate object set comprises:
filtering the first candidate object set to determine a second candidate object set, wherein a vector of information of an object in the second candidate object set is matched with the second-type condition information; and
determining the at least one object from the second candidate object set.”
(Step 2A-Prong One) The limitations of “at least one piece of second-type intention information, and the condition information further comprises second-type condition information, wherein the second-type condition information is obtained by vectorizing the at least one piece of second-type intention information; and determining the at least one object from the first candidate object set comprises: filtering the first candidate object set to determine a second candidate object set, wherein a vector of information of an object in the second candidate object set is matched with the second-type condition information; and determining the at least one object from the second candidate object set,” 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, other than reciting “model,” nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “model” language, “vectorizing,” “filtering” and “determining” in the context of this claim encompasses the user manually “at least one piece of second-type intention information, and the condition information further comprises second-type condition information, wherein the second-type condition information is obtained by vectorizing the at least one piece of second-type intention information; and determining the at least one object from the first candidate object set comprises: filtering the first candidate object set to determine a second candidate object set, wherein a vector of information of an object in the second candidate object set is matched with the second-type condition information; and determining the at least one object from the second candidate object set” in his mind.
If claim limitations, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Additionally, claim limitation “wherein the second-type condition information is obtained by vectorizing the at least one piece of second-type intention information” also fells in the grouping of “Mathematical Concepts.” Further, claim limitation “filtering the first candidate object set to determine a second candidate object set, wherein a vector of information of an object in the second candidate object set is matched with the second-type condition information” also fells in the grouping of “Managing Personal Behavior or Relationships or Interactions Between People.” Accordingly, the claim recites an abstract idea.
(Step 2A-Prong Two) and (Step 2B)
No additional elements are provided in the claim, therefore there is still no practical application and the claim does not provide significantly more as per claim 1 analysis.
For claim 5, it recites “The method according to claim 4, wherein the intention information further comprises at least one piece of third-type intention information, and the condition information further comprises third-type condition information;
determining the condition information based on the intention information comprises:
performing intention diffusion on the at least one piece of third-type intention information to obtain the third-type condition information; and
determining the at least one object from the second candidate object set comprises:
filtering the second candidate object set to determine a third candidate object set, wherein a vector of information of an object in the third candidate object set is matched with the third-type condition information; and
determining the at least one object from the third candidate object set.”
(Step 2A-Prong One) The limitations of “determining the condition information based on the intention information comprises:
performing intention diffusion on the at least one piece of third-type intention information to obtain the third-type condition information; and the determining the at least one object from the second candidate object set comprises: filtering the second candidate object set to determine a third candidate object set, wherein a vector of information of an object in the third candidate object set is matched with the third-type condition information; and determining the at least one object from the third candidate object set,” 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, other than reciting “model,” nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “model” language, “determining,” “performing,” “filtering” and “determining” in the context of this claim encompasses the user manually “determining the condition information based on the intention information comprises: performing intention diffusion on the at least one piece of third-type intention information to obtain the third-type condition information; and
the determining the at least one object from the second candidate object set comprises:
filtering the second candidate object set to determine a third candidate object set, wherein a vector of information of an object in the third candidate object set is matched with the third-type condition information; and
determining the at least one object from the third candidate object set” in his mind.
If claim limitations, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Additionally, claim limitation “filtering the second candidate object set to determine a third candidate object set, wherein a vector of information of an object in the third candidate object set is matched with the third-type condition information” also fells in the grouping of “Managing Personal Behavior or Relationships or Interactions Between People.” Accordingly, the claim recites an abstract idea.
Further, claim limitation “the condition information further comprises third-type condition information” which is merely data (e.g. contents) and does not meet any of the categories (MPEP: 2106.03, “Thus, the Federal Circuit has held that a product claim to an intangible collection of information, even if created by human effort, does not fall within any statutory category. Digitech, 758 F.3d at 1350, 111 USPQ2d at 1720 (claimed "device profile" comprising two sets of data did not meet any of the categories because it was neither a process nor a tangible product).”).
(Step 2A-Prong Two) and (Step 2B)
No additional elements are provided in the claim, therefore there is still no practical application and the claim does not provide significantly more as per claim 1 analysis.
For claim 6, it recites “The method according to claim 5, wherein the performing intention diffusion on the at least one piece of third-type intention information to obtain the third- type condition information comprises:
sending intention diffusion information to a second model, wherein the intention diffusion information is obtained based on the third-type intention information and instruction information, and the instruction information is used to indicate an intention diffusion rule;
receiving diffusion condition information sent by the second model, wherein the diffusion condition information is used to indicate a condition that an object satisfying the third-type intention information has; and
determining the third-type condition information based on the diffusion condition information.”
(Step 2A-Prong One) The limitations of “determining the third-type condition information based on the diffusion condition information,” 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, other than reciting “model,” nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “model” language, “determining” in the context of this claim encompasses the user manually “determining the third-type condition information based on the diffusion condition information” in his mind.
If claim limitations, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
(Step 2A-Prong Two) This judicial exception is not integrated into a practical application.
In particular, the claim recites additional elements – using “model” to perform the “sending,” “receiving” and “determining” steps. The “model” in these steps are recited at a high-level of generality such that they amount no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Further, the claim recites additional element – “sending intention diffusion information to a second model, wherein the intention diffusion information is obtained based on the third-type intention information and instruction information, and the instruction information is used to indicate an intention diffusion rule;
receiving diffusion condition information sent by the second model, wherein the diffusion condition information is used to indicate a condition that an object satisfying the third-type intention information has;” which is Mere data gathering or Selecting a particular data source or type of data to be manipulate and is in form of insignificant extra-solution activity (MPEP: 2106.05 (g), “iv. Obtaining information about transactions using the Internet to verify credit card transactions, CyberSource v. Retail Decisions, Inc.,” “v. Consulting and updating an activity log, Ultramercial.” “iii. Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, Electric Power Group, LLC v. Alstom S.A” and “iv. Requiring a request from a user to view an advertisement and restricting public access, Ultramercial…”).
(Step 2B) 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 using “model” to perform “sending,” “receiving” and “determining” steps amounts to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. The claim is not patent eligible.
Further, the other additional limitations “sending” and “receiving” are not sufficient to amount to significantly more than the judicial exception because “sending” and “receiving” only add well-understood, routine and conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception. For example, MPEP 2106.05(d)(II), “i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information);” “iv. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs.” “v. Analyzing DNA to provide sequence information or detect allelic variants, Genetic Techs,” and “iii. Electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225, 110 USPQ2d 1984 (2014) (creating and maintaining "shadow accounts"); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log).”
Thus, the limitation does not amount to significantly more. Even when considered in combination, these additional elements represent mere instructions to apply an exception and insignificant extra-solution activity, which do not provide an inventive concept. The claim is not patent eligible.
For claim 7, it recites “The method according to claim 5, wherein the third candidate object set comprises a third candidate object, and the filtering the second candidate object set to determine the third candidate object set comprises:
determining whether information of the third candidate object satisfies the object search information; and
determining the third candidate object as one of the at least one object in response to the information of the third candidate object satisfying the object search information.”
(Step 2A-Prong One) The limitations of “determining whether information of the third candidate object satisfies the object search information;” and “determining the third candidate object as one of the at least one object in response to the information of the third candidate object satisfying the object search information,” 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, other than reciting “model,” nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “model” language, “determining” and “determining” in the context of this claim encompasses the user manually “determining whether information of the third candidate object satisfies the object search information;” and “determining the third candidate object as one of the at least one object in response to the information of the third candidate object satisfying the object search information” in his mind.
If claim limitations, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
(Step 2A-Prong Two) and (Step 2B)
No additional elements are provided in the claim, therefore there is still no practical application and the claim does not provide significantly more as per claim 1 analysis.
For claim 8, it recites “The method according to claim 7, wherein the third candidate object set comprises a candidate object, and determining whether the information of the third candidate object satisfies the object search information comprises: obtaining information of the candidate object;
sending object determination information to a third model, wherein the object determination information is obtained based on the object search information and the information of the candidate object; and
receiving object determination result information sent by the third model, wherein the object determination result information indicates whether the information of the candidate object satisfies the object search information.”
(Step 2A-Prong Two) This judicial exception is not integrated into a practical application.
In particular, the claim recites additional elements – using “model” to perform the “obtaining,” “sending” and “receiving” steps. The “model” in these steps are recited at a high-level of generality such that they amount no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Further, the claim recites additional element – “obtaining information of the candidate object;” “sending object determination information to a third model, wherein the object determination information is obtained based on the object search information and the information of the candidate object;” and “receiving object determination result information sent by the third model, wherein the object determination result information indicates whether the information of the candidate object satisfies the object search information;” which is Mere data gathering or Selecting a particular data source or type of data to be manipulate and is in form of insignificant extra-solution activity (MPEP: 2106.05 (g), “iv. Obtaining information about transactions using the Internet to verify credit card transactions, CyberSource v. Retail Decisions, Inc.,” “v. Consulting and updating an activity log, Ultramercial.” “iii. Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, Electric Power Group, LLC v. Alstom S.A” and “iv. Requiring a request from a user to view an advertisement and restricting public access, Ultramercial…”).
(Step 2B) 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 using “model” to perform the steps amounts to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. The claim is not patent eligible.
Further, the other additional limitations “obtaining,” “sending” and “receiving” are not sufficient to amount to significantly more than the judicial exception because “obtaining,” “sending” and “receiving” only add well-understood, routine and conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception. For example, MPEP 2106.05(d)(II), “i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information);” “iv. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs.” “v. Analyzing DNA to provide sequence information or detect allelic variants, Genetic Techs,” and “iii. Electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225, 110 USPQ2d 1984 (2014) (creating and maintaining "shadow accounts"); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log).”
Thus, the limitation does not amount to significantly more. Even when considered in combination, these additional elements represent mere instructions to apply an exception and insignificant extra-solution activity, which do not provide an inventive concept. The claim is not patent eligible.
For claim 9, it recites “The method according to claim 1, wherein the object display information comprises summary information of the at least one object, and before the object display information is sent, the method further comprises:
obtaining information of the at least one object; and
summarizing information of each of the at least one object to determine summary information of each of the at least one object.”
(Step 2A-Prong One) The limitations of “summarizing information of each of the at least one object to determine summary information of each of the at least one object,” 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, other than reciting “model,” nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “model” language, “summarizing” in the context of this claim encompasses the user manually “summarizing information of each of the at least one object to determine summary information of each of the at least one object” in his mind.
If claim limitations, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
(Step 2A-Prong Two) This judicial exception is not integrated into a practical application.
In particular, the claim recites additional elements – using “model” to perform the “obtaining” and “summarizing” steps. The “model” in these steps are recited at a high-level of generality such that they amount no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Further, the claim recites additional element – “obtaining information of the at least one object;” which is Mere data gathering or Selecting a particular data source or type of data to be manipulate and is in form of insignificant extra-solution activity (MPEP: 2106.05 (g), “iv. Obtaining information about transactions using the Internet to verify credit card transactions, CyberSource v. Retail Decisions, Inc.,” “v. Consulting and updating an activity log, Ultramercial.” “iii. Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, Electric Power Group, LLC v. Alstom S.A” and “iv. Requiring a request from a user to view an advertisement and restricting public access, Ultramercial…”).
(Step 2B) 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 using “model” to perform the steps amounts to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. The claim is not patent eligible.
Further, the other additional limitations “obtaining” are not sufficient to amount to significantly more than the judicial exception because “obtaining” only add well-understood, routine and conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception. For example, MPEP 2106.05(d)(II), “i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information);” “iv. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs.” “v. Analyzing DNA to provide sequence information or detect allelic variants, Genetic Techs,” and “iii. Electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225, 110 USPQ2d 1984 (2014) (creating and maintaining "shadow accounts"); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log).”
Thus, the limitation does not amount to significantly more. Even when considered in combination, these additional elements represent mere instructions to apply an exception and insignificant extra-solution activity, which do not provide an inventive concept. The claim is not patent eligible.
For claim 10, it recites “The method according to claim 9, wherein the at least one object comprises a first object, and determining summary information of each of the at least one object comprises:
determining first-type display information and second-type display information based on information of the first object, wherein a length of the second-type display information is greater than a length of the first-type display information;
summarizing the second-type display information; and
determining summary information of the first object based on the first-type display information and the second-type display information that is summarized.”
(Step 2A-Prong One) The limitations of “determining first-type display information and second-type display information based on information of the first object, wherein a length of the second-type display information is greater than a length of the first-type display information;” “summarizing the second-type display information;” and “determining summary information of the first object based on the first-type display information and the second-type display information that is summarized,” 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, other than reciting “model,” nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “model” language, “determining,” “summarizing” and “determining” in the context of this claim encompasses the user manually “determining first-type display information and second-type display information based on information of the first object, wherein a length of the second-type display information is greater than a length of the first-type display information;” “summarizing the second-type display information;” and “determining summary information of the first object based on the first-type display information and the second-type display information that is summarized” in his mind.
If claim limitations, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
(Step 2A-Prong Two) and (Step 2B)
No additional elements are provided in the claim, therefore there is still no practical application and the claim does not provide significantly more as per claim 1 analysis.
For claim 11, it recites “The method according to claim 10, wherein the summarizing the second- type display information comprises:
sending original display information to a fourth model, wherein the original display information is determined based on the second-type display information; and
receiving display summary information sent by the fourth model, wherein the display summary information comprises the second-type display information that is summarized.”
(Step 2A-Prong Two) This judicial exception is not integrated into a practical application.
In particular, the claim recites additional elements – using “model” to perform the “sending” and “receiving” steps. The “model” in these steps are recited at a high-level of generality such that they amount no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Further, the claim recites additional element – “sending original display information to a fourth model, wherein the original display information is determined based on the second-type display information;” and “receiving display summary information sent by the fourth model, wherein the display summary information comprises the second-type display information that is summarized;” which is Mere data gathering or Selecting a particular data source or type of data to be manipulate and is in form of insignificant extra-solution activity (MPEP: 2106.05 (g), “iv. Obtaining information about transactions using the Internet to verify credit card transactions, CyberSource v. Retail Decisions, Inc.,” “v. Consulting and updating an activity log, Ultramercial.” “iii. Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, Electric Power Group, LLC v. Alstom S.A” and “iv. Requiring a request from a user to view an advertisement and restricting public access, Ultramercial…”).
(Step 2B) 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 using “model” to perform the steps amounts to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. The claim is not patent eligible.
Further, the other additional limitations “sending” and “receiving” are not sufficient to amount to significantly more than the judicial exception because “sending” and “receiving” only add well-understood, routine and conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception. For example, MPEP 2106.05(d)(II), “i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information);” “iv. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs.” “v. Analyzing DNA to provide sequence information or detect allelic variants, Genetic Techs,” and “iii. Electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225, 110 USPQ2d 1984 (2014) (creating and maintaining "shadow accounts"); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log).”
Thus, the limitation does not amount to significantly more. Even when considered in combination, these additional elements represent mere instructions to apply an exception and insignificant extra-solution activity, which do not provide an inventive concept. The claim is not patent eligible.
For claim 17, it is a device claim having similar limitations as recited in claim 1. Thus, claim 17 is also rejected under the same rationale as cited in the rejection of rejected claim 1.
For claim 18, it is a device claim having similar limitations as recited in claim 2. Thus, claim 18 is also rejected under the same rationale as cited in the rejection of rejected claim 2.
For claim 19, it is a device claim having similar limitations as recited in claim 9. Thus, claim 19 is also rejected under the same rationale as cited in the rejection of rejected claim 9.
For claim 20, it recites “A computer-readable storage medium, on which computer programs are stored, wherein the computer programs, when executed by a processor, implement the method according to claim 1”
(Step 2A-Prong Two) This judicial exception is not integrated into a practical application.
In particular, the claim recites additional elements – using “computer-readable storage medium” and “processor” to perform the steps. The “computer-readable storage medium” and “processor” in these steps are recited at a high-level of generality such that they amount no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
(Step 2B) 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 using “computer-readable storage medium” and “processor” to perform the steps amounts to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. The claim is not patent eligible.
Thus, the limitation does not amount to significantly more. Even when considered in combination, these additional elements represent mere instructions to apply an exception and insignificant extra-solution activity, which do not provide an inventive concept. The claim is not patent eligible.
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 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.
Claims 1, 17 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Tang et al. (U.S. Pub. No.: US 20210141839, hereinafter Tang), in view of Mourya et al. (U.S. Pub. No.: US 20230351257, hereinafter Mourya).
For claim 1, Tang discloses a data processing method, comprising:
obtaining object search information (Tang: paragraph [0008], “…receiving a search word sent by a user by using a client…”);
sending intention analysis information to a first model, wherein the intention analysis information is generated based on the object search information (Tang: paragraph [0009], “Optionally, recognizing search intention of the user according to feature information of the search word and/or search context feature information includes: acquiring the feature information of the search word and/or the search context feature information; determining non-local search preference of the user according to the feature information of the search word and/or the search context feature information and by using a pre-trained non-local search preference determination model; and determining the search intention of the user according to the non-local search preference and a preset preference threshold condition”
paragraph [0023], “Optionally, the search intention recognition module is specifically configured to: acquire the feature information of the search word and/or the search context feature information; determine non-local search preference of the user according to the feature information of the search word and/or the search context feature information and by using a pre-trained non-local search preference determination model; and determine the search intention of the user according to the non-local search preference and a preset preference threshold condition”);
receiving intention information sent by the first model, wherein the intention information is determined based on the object search information (Tang: paragraph [0009], “Optionally, recognizing search intention of the user according to feature information of the search word and/or search context feature information includes: acquiring the feature information of the search word and/or the search context feature information; determining non-local search preference of the user according to the feature information of the search word and/or the search context feature information and by using a pre-trained non-local search preference determination model; and determining the search intention of the user according to the non-local search preference and a preset preference threshold condition”
paragraph [0056], “[0056] step S103: perform search by using a search policy corresponding to the search intention and according to the search word to acquire information search results associated with the search word, where the information search results include a local search result and/or a non-local search result…” Also see Fig. 1); and
generating object display information, wherein the object display information is determined based on information of at least one object, the object is determined based on the intention information, and the object is matched with the object search information (Tang: paragraph [0009], “Optionally, recognizing search intention of the user according to feature information of the search word and/or search context feature information includes: acquiring the feature information of the search word and/or the search context feature information; determining non-local search preference of the user according to the feature information of the search word and/or the search context feature information and by using a pre-trained non-local search preference determination model; and determining the search intention of the user according to the non-local search preference and a preset preference threshold condition”
paragraph [0056], “[0056] step S103: perform search by using a search policy corresponding to the search intention and according to the search word to acquire information search results associated with the search word, where the information search results include a local search result and/or a non-local search result…” paragraph [0057], “Step S104: send the information search results to the client, so that the client displays the information search results”
paragraph [0058], “In the first embodiment of the present disclosure, the user enters the search word on the client. After monitoring the entered search word, the client sends the search word to a server to perform search. After receiving the search word, the server first needs to recognize the search intention to determine the search intention of the user, and then performs search by using the corresponding search policy according to the search intention of the user;
wherein after the intention information is received and before the object display information is sent, the method further comprises: determining condition information based on the intention information (Tang: paragraph [0008], “…performing search by using a search policy corresponding to the recognized search intention and according to the search word to acquire information search results associated with the search word, where the information search results include a local search result and/or a non-local search result; and sending the information search results to the client, so that the client displays the information search results,” where “condition information” is broadly interpreted as “search policy” Also see Fig. 1, step S103, which is after recognize search intention of the user (step S102), and before send the information search results to the client (step S104)); and
determining the at least one object based on the condition information, wherein information of each object among the at least one object is matched with the condition information (Tang: paragraph [0008], “…performing search by using a search policy corresponding to the recognized search intention and according to the search word to acquire information search results associated with the search word, where the information search results include a local search result and/or a non-local search result; and sending the information search results to the client, so that the client displays the information search results,” where “condition information” is broadly interpreted as “search policy” Also see Fig. 1).
However, Tang does not explicitly disclose, wherein the object search information is information described in an unstructured language; and
the first model is a model having a natural language processing function; and
the intention information is implemented in a form of a Key-Value pair.
Mourya discloses wherein the object search information is information described in an unstructured language (Mourya: paragraph [0002], “…The virtual agent is designed to communicate with users in a natural language format, typically through text-based chat interfaces…”
paragraph [0052], “…FIG. 1 illustrates a use case 100 of a user 102 interaction with a virtual agent 104, in accordance with an example embodiment. In an embodiment. The interaction begins when the user 102 provides input to the virtual agent 104 through a medium 106. The medium 106 for communication between the user 110 and the human agent 112 may be either in a form of voice or text. The user 102 may be, for example, a customer, client, or any other person seeking information or assistance through the virtual agent 104.”
paragraphs [0185]-[0186], “…[0185] Natural Language Processing (NLP): NLP techniques are used to process and analyze the text data present in the fallback logs. These techniques include tasks such as tokenization, part-of-speech tagging, named entity recognition, sentiment analysis, and topic modeling. NLP helps extract linguistic features, understand the context, and derive meaningful information from the user queries. [0186] Text Mining: Text mining techniques focus on extracting useful information unstructured text data.”); and
the first model is a model having a natural language processing function (Mourya: paragraph [0003], “…The virtual agent may utilize various techniques such as natural language processing (NLP), machine learning, pattern recognition, and knowledge representation to achieve accurate understanding and effective communication with users.” paragraph [0050], “…The term “virtual agent” may be used to refer to a virtual assistant that is computer program or AI system designed to simulate human-like conversations with users. They are typically powered by artificial intelligence and natural language processing technologies. The virtual agent can understand user inputs, generate appropriate responses, and perform specific tasks or provide information. They are often used in customer support, information retrieval, and other applications to provide automated and efficient conversational experiences.”
paragraph [0084], “…utilizes natural language understanding techniques to analyze and process the user's query. These techniques may involve tokenization, part-of-speech tagging, entity recognition, and other NLU processes to extract meaningful information from the query”
paragraphs [0185]-[0186], “…[0185] Natural Language Processing (NLP): NLP techniques are used to process and analyze the text data present in the fallback logs. These techniques include tasks such as tokenization, part-of-speech tagging, named entity recognition, sentiment analysis, and topic modeling. NLP helps extract linguistic features, understand the context, and derive meaningful information from the user queries. [0186] Text Mining: Text mining techniques focus on extracting useful information unstructured text data.”); and
the intention information is implemented in a form of a Key-Value pair (Mourya: paragraph [0228], “…For example, the list of optimal utterances, similar utterances, and intent options may be stored as arrays or lists. [0230] Dictionaries/Maps: Dictionaries or maps may be used to store key-value pairs for efficient retrieval and management of data.”);
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to improve upon “INFORMATION SEARCH METHOD, APPARATUS, AND SYSTEM” as taught by Tang by implementing “METHOD AND SYSTEM FOR TRAINING VIRTUAL AGENTS THROUGH FALLBACK ANALYSIS” as taught by Coden, because it would provide Tang’s method with the enhanced capability of “…NLP helps extract linguistic features, understand the context, and derive meaningful information from the user queries…” (Mourya: paragraph [0184]) and “…store key-value pairs for efficient retrieval and management of data.” (Mourya: paragraph [0228]).
For claim 17, it is a device claim having similar limitations as recited in claim 1. Thus, claim 17 is also rejected under the same rationale as cited in the rejection of rejected claim 1.
For claim 20, Tang discloses a computer-readable storage medium, on which computer programs are stored, wherein the computer programs, when executed by a processor, implement the method according to claim 1 (Tang: column 5, lines 60-67, “According to a sixth aspect, an embodiment of the present disclosure further provides a computer device, including a memory, a processor, and computer programs stored in the memory and executable by the processor. When executing the computer programs, the processor is caused to perform the steps of the method in the first aspect”).
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Tang et al. (U.S. Pub. No.: US 20210141839, hereinafter Tang), in view of Mourya et al. (U.S. Pub. No.: US 20230351257, hereinafter Mourya), and further in view of Coden et al. (U.S. Patent No.: US 6341277, hereinafter Coden).
For claim 3, Tang and Coden disclose the method according to claim 2, wherein the intention information comprises at least one piece of first-type intention information, and the condition information comprises first-type condition information, wherein the first-type intention information is used to describe the first-type condition information (Coden: column 35, liens 30-50, “(416) Example: The user query is: return the ID, START and STOP of all records for which the film producer is HITCHCOCK. For this example it is assumed that there is a table which has also a column named PRODUCER. The Query Object comprises of a list of result columns: ID, START, STOP which are fully qualified to uniquely identify the table(s) from which the records are to be chosen, a list of conditions which are to be satisfied (e.g. PRODUCER=HITCHCOCK) and a method createSQL which translates the user query into a SQL statement. A Query Object contains also other methods which are helpful in writing applications using them, e.g. a method to execute this query against a database and methods which transform the results into a form convenient for the user interface. There could be many different implementations of a query object, however this is the preferred method” where “first-type intention information” and “first-type condition information” are broadly interpreted as “the film producer is HITCHCOCK,” “a table which has also a column named PRODUCER” and “PRODUCER=HITCHCOCK”);
the method further comprises:
determining the at least one object from an object information database, and the determining the at least one object from the object information database comprise: determining a first candidate object set from an original object set based on the first- type condition information, wherein information of an object in the first candidate object set is matched with the first-type condition information (Coden: column 35, liens 30-50, “(416) Example: The user query is: return the ID, START and STOP of all records for which the film producer is HITCHCOCK. For this example it is assumed that there is a table which has also a column named PRODUCER. The Query Object comprises of a list of result columns: ID, START, STOP which are fully qualified to uniquely identify the table(s) from which the records are to be chosen, a list of conditions which are to be satisfied (e.g. PRODUCER=HITCHCOCK) and a method createSQL which translates the user query into a SQL statement. A Query Object contains also other methods which are helpful in writing applications using them, e.g. a method to execute this query against a database and methods which transform the results into a form convenient for the user interface. There could be many different implementations of a query object, however this is the preferred method”); and
determining the at least one object from the first candidate object set (Coden: column 35, liens 30-50, “(416) Example: The user query is: return the ID, START and STOP of all records for which the film producer is HITCHCOCK. For this example it is assumed that there is a table which has also a column named PRODUCER. The Query Object comprises of a list of result columns: ID, START, STOP which are fully qualified to uniquely identify the table(s) from which the records are to be chosen, a list of conditions which are to be satisfied (e.g. PRODUCER=HITCHCOCK) and a method createSQL which translates the user query into a SQL statement. A Query Object contains also other methods which are helpful in writing applications using them, e.g. a method to execute this query against a database and methods which transform the results into a form convenient for the user interface. There could be many different implementations of a query object, however this is the preferred method”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to improve upon “INFORMATION SEARCH METHOD, APPARATUS, AND SYSTEM” as taught by Tang by implementing “Object Oriented Query Model And Process For Complex Heterogeneous Database Queries” as taught by Coden, because it would provide Tang’s method with the enhanced capability of “…the input in the GUI is translated into a single compound query object…” (Coden: column 2, liens 30-35) and “…to uniquely identify the table(s) from which the records are to be chosen, a list of conditions which are to be satisfied (e.g. PRODUCER=HITCHCOCK) and a method createSQL which translates the user query into a SQL statement.” (Coden: column 35, liens 30-50).
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Tang et al. (U.S. Pub. No.: US 20210141839, hereinafter Tang), in view of Mourya et al. (U.S. Pub. No.: US 20230351257, hereinafter Mourya), and further in view of Coden et al. (U.S. Patent No.: US 6341277, hereinafter Coden), and further in view of Nivelet (U.S. Pub. No.: US 20040002968).
For claim 4, Tang and Coden disclose the method according to claim 3, wherein the intention information further comprises at least one piece of second-type intention information, and the condition information further comprises second-type condition information, wherein the second-type condition information is obtained by vectorizing the at least one piece of second-type intention information (Coden: column 35, liens 30-50, “(416) Example: The user query is: return the ID, START and STOP of all records for which the film producer is HITCHCOCK. For this example it is assumed that there is a table which has also a column named PRODUCER. The Query Object comprises of a list of result columns: ID, START, STOP which are fully qualified to uniquely identify the table(s) from which the records are to be chosen, a list of conditions which are to be satisfied (e.g. PRODUCER=HITCHCOCK) and a method createSQL which translates the user query into a SQL statement. A Query Object contains also other methods which are helpful in writing applications using them, e.g. a method to execute this query against a database and methods which transform the results into a form convenient for the user interface. There could be many different implementations of a query object, however this is the preferred method” Column 21, lines 30-35, “…convert the component_results vector…” Column 37, line 40-column 38, line 9, “…The Compound Query contains a list of Query Objects, Operator Objects and Parenthesis Objects which form a Boolean expression in infix notation. The first step is to translate the Boolean expression from infix notation to post fix notation, an algorithm which is extensively described in the literature…add CTE object to Vector v”); and
the determining the at least one object from the first candidate object set comprises: filtering the first candidate object set to determine a second candidate object set, wherein a vector of information of an object in the second candidate object set is matched with the second-type condition information; and determining the at least one object from the second candidate object set (Coden: column 35, liens 30-50, “(416) Example: The user query is: return the ID, START and STOP of all records for which the film producer is HITCHCOCK. For this example it is assumed that there is a table which has also a column named PRODUCER. The Query Object comprises of a list of result columns: ID, START, STOP which are fully qualified to uniquely identify the table(s) from which the records are to be chosen, a list of conditions which are to be satisfied (e.g. PRODUCER=HITCHCOCK) and a method createSQL which translates the user query into a SQL statement. A Query Object contains also other methods which are helpful in writing applications using them, e.g. a method to execute this query against a database and methods which transform the results into a form convenient for the user interface. There could be many different implementations of a query object, however this is the preferred method” Column 37, line 40-column 38, line 9, “…The Compound Query contains a list of Query Objects, Operator Objects and Parenthesis Objects which form a Boolean expression in infix notation. The first step is to translate the Boolean expression from infix notation to post fix notation, an algorithm which is extensively described in the literature…add CTE object to Vector v”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to improve upon “INFORMATION SEARCH METHOD, APPARATUS, AND SYSTEM” as taught by Tang by implementing “Object Oriented Query Model And Process For Complex Heterogeneous Database Queries” as taught by Coden, because it would provide Tang’s method with the enhanced capability of “…the input in the GUI is translated into a single compound query object…” (Coden: column 2, liens 30-35) and “…to uniquely identify the table(s) from which the records are to be chosen, a list of conditions which are to be satisfied (e.g. PRODUCER=HITCHCOCK) and a method createSQL which translates the user query into a SQL statement.” (Coden: column 35, liens 30-50).
However, Tang and Coden do not explicitly disclose vectorizing.
Nivelet discloses vectorizing (Nivelet: column 35, liens 30-50, “(416) Example: The user query is: return the ID, START and STOP of all records for which the film producer is HITCHCOCK. For this example it is assumed that there is a table which has also a column named PRODUCER. The Query Object comprises of a list of result columns: ID, START, STOP which are fully qualified to uniquely identify the table(s) from which the records are to be chosen, a list of conditions which are to be satisfied (e.g. PRODUCER=HITCHCOCK) and a method createSQL which translates the user query into a SQL statement. A Query Object contains also other methods which are helpful in writing applications using them, e.g. a method to execute this query against a database and methods which transform the results into a form convenient for the user interface. There could be many different implementations of a query object, however this is the preferred method” Column 37, line 40-column 38, line 9, “…The Compound Query contains a list of Query Objects, Operator Objects and Parenthesis Objects which form a Boolean expression in infix notation. The first step is to translate the Boolean expression from infix notation to post fix notation, an algorithm which is extensively described in the literature…add CTE object to Vector v”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to improve upon “INFORMATION SEARCH METHOD, APPARATUS, AND SYSTEM” as taught by Tang by implementing “Method For Preconditioning And Encoding A Data Table, And Method For The Implementation Of Table Requests On A Vectoral Processor” as taught by Nivelet, because it would provide Tang’s modified method with the enhanced capability of “…for searching for records in a data table in response to a given query, consisting of installing a copy of the table of numeric values obtained via the preceding method in a machine with vectorial capability performing the processing of the numeric values of the table in accordance with the query served by the decision application server.” (Nivelet: paragraph [0022])
Claims 9 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Tang et al. (U.S. Pub. No.: US 20210141839, hereinafter Tang), in view of Mourya et al. (U.S. Pub. No.: US 20230351257, hereinafter Mourya), and further in view of Koukoumidis et al. (U.S. Patent No.: US 11245646, hereinafter Koukoumidis).
For claim 9, Tang discloses the method according to claim 1.
However, Tang does not explicitly disclose , wherein the object display information comprises summary information of the at least one object, and before the object display information is sent, the method further comprises:
obtaining information of the at least one object; and
summarizing information of each of the at least one object to determine summary information of each of the at least one object.
Koukoumidis discloses, wherein the object display information comprises summary information of the at least one object, and before the object display information is sent, the method further comprises: obtaining information of the at least one object (Koukoumidis: column 10, lines 61-67, “FIG. 2…the assistant system 140 may assist a user to obtain information or services.” column 11, lines 5-30, “In particular embodiments, the assistant system 140 may further assist the user to effectively and efficiently digest the obtained information by summarizing the information.”); and
summarizing information of each of the at least one object to determine summary information of each of the at least one object (Koukoumidis: column 10, lines 61-67, “FIG. 2…the assistant system 140 may assist a user to obtain information or services.” column 11, lines 5-30, “…the assistant system 140 may further assist the user to effectively and efficiently digest the obtained information by summarizing the information.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to improve upon “INFORMATION SEARCH METHOD, APPARATUS, AND SYSTEM” as taught by Tang by implementing “Predictive Injection Of Conversation Fillers For Assistant Systems” as taught by Koukoumidis, because it would provide Tang’s modified method with the enhanced capability of “…to effectively and efficiently digest the obtained information by summarizing the information.” (Koukoumidis: column 11, lines 5-30).
For claim 19, it is a device claim having similar limitations as recited in claim 9. Thus, claim 19 is also rejected under the same rationale as cited in the rejection of rejected claim 9.
Claims 10 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Tang et al. (U.S. Pub. No.: US 20210141839, hereinafter Tang), in view of Mourya et al. (U.S. Pub. No.: US 20230351257, hereinafter Mourya), and further in view of Koukoumidis et al. (U.S. Patent No.: US 11245646, hereinafter Koukoumidis), and further in view of Nelson et al. (U.S. Patent No.: US 6243713, hereinafter Nelson).
For claim 10, Tang and Koukoumidis disclose the method according to claim 9, wherein the at least one object comprises a first object, and the determining summary information of each of the at least one object comprises:
determining display information based on information of the first object, wherein a length of the second-type display information is greater than a length of the first-type display information (Koukoumidis: column 10, lines 61-67, “FIG. 2…the assistant system 140 may assist a user to obtain information or services.” column 11, lines 5-30, “…the assistant system 140 may further assist the user to effectively and efficiently digest the obtained information by summarizing the information.”);
summarizing the second-type display information (Koukoumidis: column 10, lines 61-67, “FIG. 2…the assistant system 140 may assist a user to obtain information or services.” column 11, lines 5-30, “…the assistant system 140 may further assist the user to effectively and efficiently digest the obtained information by summarizing the information.”); and
determining summary information of the first object based on the first-type display information and the second-type display information that is summarized (Koukoumidis: column 10, lines 61-67, “FIG. 2…the assistant system 140 may assist a user to obtain information or services.” column 11, lines 5-30, “…the assistant system 140 may further assist the user to effectively and efficiently digest the obtained information by summarizing the information.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to improve upon “INFORMATION SEARCH METHOD, APPARATUS, AND SYSTEM” as taught by Tang by implementing “Predictive Injection Of Conversation Fillers For Assistant Systems” as taught by Koukoumidis, because it would provide Tang’s modified method with the enhanced capability of “…to effectively and efficiently digest the obtained information by summarizing the information.” (Koukoumidis: column 11, lines 5-30).
However, Tang and Koukoumidis do not explicitly disclose comprises: first-type display information and second-type display information based on information of the first object
Nelson discloses comprises: first-type display information and second-type display information based on information of the first object (Nelson: column 7, lines 61-67, “These search results 210 are then presented to the user in a suitable user interface that allows the user to retrieve and browse the documents. Presentation may include a succinct listing of document title, author, date, score, document summary, and so forth, as deemed useful to the user…”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to improve upon “INFORMATION SEARCH METHOD, APPARATUS, AND SYSTEM” as taught by Tang by implementing “Multimedia Document Retrieval By Application Of Multimedia Queries To A Unified Index Of Multimedia Data For A Plurality Of Multimedia Data Types” as taught by Nelson, because it would provide Tang’s modified method with the enhanced capability of “…Presentation may include a succinct listing of document title, author, date, score, document summary, and so forth, as deemed useful to the user…” (Nelson: column 7, lines 61-67).
For claim 11, Tang, Koukoumidis and Nelson disclose the method according to claim 10, wherein the summarizing the second- type display information comprises:
sending original display information to a fourth model, wherein the original display information is determined based on the second-type display information; and receiving display summary information sent by the fourth model, wherein the display summary information comprises the second-type display information that is summarized (Koukoumidis: column 10, lines 61-67, “FIG. 2…the assistant system 140 may assist a user to obtain information or services.” column 11, lines 5-30, “…the assistant system 140 may further assist the user to effectively and efficiently digest the obtained information by summarizing the information.” Where “fourth model” is broadly interpreted as “assistant system”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to improve upon “INFORMATION SEARCH METHOD, APPARATUS, AND SYSTEM” as taught by Tang by implementing “Predictive Injection Of Conversation Fillers For Assistant Systems” as taught by Koukoumidis, because it would provide Tang’s modified method with the enhanced capability of “…to effectively and efficiently digest the obtained information by summarizing the information.” (Koukoumidis: column 11, lines 5-30).
Allowable Subject Matter
Claims 5-8 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 101, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/YU ZHAO/Primary Examiner, Art Unit 2169
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