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 .
This action is responsive to the application filed 04/22/2024. Claims 1-13 are presented for examination.
Priority
Applicant’s claim for the benefit of a prior filed application PCT/JP2021/041587, filed 11/11/2021, is acknowledged.
Information Disclosure Statement
The information disclosure statements (IDS) submitted 04/22/2024 & 01/17/2025, have been considered by the examiner.
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 therefore, subject to the conditions and requirements of this title.
Claims 1-13 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1
Step 1: The claim recites “An information processing apparatus comprising:”; therefore, it is directed to the statutory category of a machine.
Step 2A Prong 1: The claim recites, inter alia:
an evaluation process of evaluating a degree of similarity between objects included in the set of objects and identifying one or a plurality of similar objects which are similar to a prediction target object: These limitations recite a mentally performable process with the aid of pen and paper of using observation, judgement, and evaluation to evaluate a degree of similarity between objects included in the set of objects and identifying one or a plurality of similar objects which are similar to a prediction target object.
and a prediction process of determining a label to be given to the prediction target object with reference to a similar label(s), the similar label(s) being a label(s) which is/are given to each of the one or a plurality of similar objects and which has/have been predicted by a prediction model: These limitations recite mathematical calculations similar to how a step of "determining" a variable or number using mathematical methods or "performing" a mathematical operation may also be considered mathematical calculations when the broadest reasonable interpretation of the claim in light of the specification encompasses a mathematical calculation per MPEP 2106.04(a)(2)(I)(C).
Thus, the claim recites a judicial exception.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The additional elements of the claim are as follows:
at least one processor, the at least one processor being configured to carry out: These additional elements are recited at a high level of generality and amount to invoking computers or other machinery merely as a tool to apply the underlying judicial exception. See MPEP § 2106.05(f).
an acquisition process of means for acquiring a set of objects: These additional elements amount to insignificant extra-solution activity in the form of mere data gathering per MPEP § 2106.05(g).
Thus, the way in which the additional elements use or interact with the judicial exception do not integrate the judicial exception into a practical application.
Step 2B: The additional elements from Step 2A Prong 2 include invoking generic computer components to apply the underlying judicial exception and insignificant extra-solution activity of data gathering recited by “an acquisition process of means for acquiring a set of objects” which are well-understood routine and conventional activities similar to presenting offers and gathering statistics per MPEP 2106.05(d)(II). Thus, the additional elements, viewed individually or in combination, do not provide an inventive concept or otherwise amount to significantly more than the abstract idea itself. See MPEP § 2106.05.
Claim 2
Step 1: A machine, as above.
Step 2A Prong 1: The claim recites the abstract ideas of claim 1, as well as inter alia:
calculate a respective score(s) of the similar label(s): These limitations recite mathematical calculations similar to how a step of "determining" a variable or number using mathematical methods or "performing" a mathematical operation may also be considered mathematical calculations when the broadest reasonable interpretation of the claim in light of the specification encompasses a mathematical calculation per MPEP 2106.04(a)(2)(I)(C).
determine the label to be given to the prediction target object with further reference to the score(s): These limitations recite a mentally performable process with the aid of pen and paper of using judgement and evaluation to determine the label to be given to the prediction target object with further reference to the scores.
Thus, the claim recites a judicial exception.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The additional elements of the claim are as follows:
the at least one processor is configured to: These additional elements are recited at a high level of generality and amount to invoking computers or other machinery merely as a tool to apply the underlying judicial exception. See MPEP § 2106.05(f).
the at least one processor is configured to: These additional elements are recited at a high level of generality and amount to invoking computers or other machinery merely as a tool to apply the underlying judicial exception. See MPEP § 2106.05(f).
Thus, the way in which the additional elements use or interact with the judicial exception do not integrate the judicial exception into a practical application.
Step 2B: The additional elements from Step 2A Prong 2 include invoking generic computer components to apply the underlying judicial exception. Thus, the additional elements, viewed individually or in combination, do not provide an inventive concept or otherwise amount to significantly more than the abstract idea itself. See MPEP § 2106.05.
Claim 3
Step 1: A machine, as above.
Step 2A Prong 1: The claim recites the abstract ideas of claim 1, as well as inter alia:
predict a yet-to-be-modified label of the prediction target object with use of the prediction model; predict the similar label(s) with use of the prediction model: These limitations recite mathematical calculations similar to how a step of "determining" a variable or number using mathematical methods or "performing" a mathematical operation may also be considered mathematical calculations when the broadest reasonable interpretation of the claim in light of the specification encompasses a mathematical calculation per MPEP 2106.04(a)(2)(I)(C).
determine, as the label to be given to the prediction target object, a modified label that is obtained by modifying the yet-to-be-modified label with reference to the similar label(s): These limitations recite a mentally performable process with the aid of pen and paper of using judgement and evaluation to determine, as the label to be given to the prediction target object, a modified label that is obtained by modifying the yet-to-be-modified label with reference to the similar label(s).
Thus, the claim recites a judicial exception.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The additional elements of the claim are as follows:
wherein in the prediction process, the at least one processor is configured to: These additional elements are recited at a high level of generality and amount to invoking computers or other machinery merely as a tool to apply the underlying judicial exception. See MPEP § 2106.05(f).
Thus, the way in which the additional elements use or interact with the judicial exception do not integrate the judicial exception into a practical application.
Step 2B: The additional elements from Step 2A Prong 2 include invoking generic computer components to apply the underlying judicial exception. Thus, the additional elements, viewed individually or in combination, do not provide an inventive concept or otherwise amount to significantly more than the abstract idea itself. See MPEP § 2106.05.
Claim 4
Step 1: A machine, as above.
Step 2A Prong 1: The claim recites the abstract ideas of claim 3, as well as inter alia:
identifies a plurality of similar objects: These limitations recite a mentally performable process with the aid of pen and paper of using observation and judgement to identify a plurality of similar objects.
extract one or more similar labels from a plurality of similar labels given to the plurality of similar objects: These limitations recite a mentally performable process with the aid of pen and paper of using observation and judgement to extract one or more similar labels from a plurality of similar labels given to the plurality of similar objects.
and carry out a comparison between the extracted one or more similar labels and the yet-to-be-modified label to determine the modified label: These limitations recite a mentally performable process with the aid of pen and paper of using observation, judgement, and evaluation to carry out a comparison between the extracted one or more similar labels and the yet-to-be-modified label to determine the modified label.
Thus, the claim recites a judicial exception.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The additional elements of the claim are as follows:
the at least one processor: These additional elements are recited at a high level of generality and amount to invoking computers or other machinery merely as a tool to apply the underlying judicial exception. See MPEP § 2106.05(f).
the at least one processor: These additional elements are recited at a high level of generality and amount to invoking computers or other machinery merely as a tool to apply the underlying judicial exception. See MPEP § 2106.05(f).
Thus, the way in which the additional elements use or interact with the judicial exception do not integrate the judicial exception into a practical application.
Step 2B: The additional elements from Step 2A Prong 2 include invoking generic computer components to apply the underlying judicial exception. Thus, the additional elements, viewed individually or in combination, do not provide an inventive concept or otherwise amount to significantly more than the abstract idea itself. See MPEP § 2106.05.
Claim 5
Step 1: A machine, as above.
Step 2A Prong 1: The claim recites the abstract ideas of claim 3, as well as inter alia:
sort the plurality of similar labels given to the plurality of similar objects with reference to the plurality of similar labels given to the plurality of similar objects and the respective scores of the similar labels: These limitations recite a mentally performable process with the aid of pen and paper of using observation and judgement to sort the plurality of similar labels given to the plurality of similar objects with reference to the plurality of similar labels given to the plurality of similar objects and the respective scores of the similar labels.
sort a plurality of yet-to-be-modified labels related to the prediction target object with reference to the plurality of yet-to-be-modified labels related to the prediction target object and the respective scores of the yet-to-be-modified labels: These limitations recite a mentally performable process with the aid of pen and paper of using observation and judgement to sort a plurality of yet-to-be-modified labels related to the prediction target object with reference to the plurality of yet-to-be-modified labels related to the prediction target object and the respective scores of the yet-to-be-modified labels.
and determine, as the modified labels, the yet-to-be-modified labels included in M (M is a natural number) top-ranked similar labels given to the plurality of similar objects among N (N is a natural number) top-ranked yet-to-be-modified labels related to the prediction target object: These limitations recite a mentally performable process with the aid of pen and paper of using judgement and evaluation to determine, as the modified labels, the yet-to-be-modified labels included in M (M is a natural number) top-ranked similar labels given to the plurality of similar objects among N (N is a natural number) top-ranked yet-to-be-modified labels related to the prediction target object.
Thus, the claim recites a judicial exception.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The additional elements of the claim are as follows:
the at least one processor is configured to: These additional elements are recited at a high level of generality and amount to invoking computers or other machinery merely as a tool to apply the underlying judicial exception. See MPEP § 2106.05(f).
the at least one processor is configured to: These additional elements are recited at a high level of generality and amount to invoking computers or other machinery merely as a tool to apply the underlying judicial exception. See MPEP § 2106.05(f).
Thus, the way in which the additional elements use or interact with the judicial exception do not integrate the judicial exception into a practical application.
Step 2B: The additional elements from Step 2A Prong 2 include invoking generic computer components to apply the underlying judicial exception. Thus, the additional elements, viewed individually or in combination, do not provide an inventive concept or otherwise amount to significantly more than the abstract idea itself. See MPEP § 2106.05.
Claim 6
Step 1: A machine, as above.
Step 2A Prong 1: The claim recites the abstract ideas of claim 5, as well as inter alia:
further sort the plurality of similar labels given to the plurality of similar objects with reference to a hierarchical relationship between the plurality of similar labels: These limitations recite a mentally performable process with the aid of pen and paper of using observation and judgement to further sort the plurality of similar labels given to the plurality of similar objects with reference to a hierarchical relationship between the plurality of similar labels.
and determine, as the modified labels, the yet-to-be-modified labels included in M (M is a natural number) top-ranked similar labels given to the plurality of similar objects among N (N is a natural number) top-ranked yet-to-be-modified labels related to the prediction target object: These limitations recite a mentally performable process with the aid of pen and paper of using judgement and evaluation to determine, as the modified labels, the yet-to-be-modified labels included in M (M is a natural number) top-ranked similar labels given to the plurality of similar objects among N (N is a natural number) top-ranked yet-to-be-modified labels related to the prediction target object.
Thus, the claim recites a judicial exception.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The additional elements of the claim are as follows:
the at least one processor is configured to: These additional elements are recited at a high level of generality and amount to invoking computers or other machinery merely as a tool to apply the underlying judicial exception. See MPEP § 2106.05(f).
Thus, the way in which the additional elements use or interact with the judicial exception do not integrate the judicial exception into a practical application.
Step 2B: The additional elements from Step 2A Prong 2 include invoking generic computer components to apply the underlying judicial exception. Thus, the additional elements, viewed individually or in combination, do not provide an inventive concept or otherwise amount to significantly more than the abstract idea itself. See MPEP § 2106.05.
Claim 7
Step 1: A machine, as above.
Step 2A Prong 1: The claim recites the abstract ideas of claim 1, as well as inter alia:
identify the one or more similar objects by outputting a graph representing a similarity relationship between the objects: These limitations recite mathematical relationships similar to organizing information and manipulating information through mathematical correlations per MPEP 2106.04(a)(2)(I)(A)(iv).
and determine the label to be given to the prediction target object with reference to the similar label(s) given to the extracted one or more similar objects: These limitations recite a mentally performable process with the aid of pen and paper of using judgement and evaluation to determine the label to be given to the prediction target object with reference to the similar label(s) given to the extracted one or more similar objects.
Thus, the claim recites a judicial exception.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The additional elements of the claim are as follows:
wherein in the evaluation process, the at least one processor is configured to: These additional elements are recited at a high level of generality and amount to invoking computers or other machinery merely as a tool to apply the underlying judicial exception. See MPEP § 2106.05(f).
wherein in the prediction process, the at least one processor is configured to: These additional elements are recited at a high level of generality and amount to invoking computers or other machinery merely as a tool to apply the underlying judicial exception. See MPEP § 2106.05(f).
extract one or more similar objects that exist within a predetermined number of hops from the prediction target object with reference to the graph: These additional elements amount to insignificant extra-solution activity in the form of selecting a particular data source or type of data to be manipulated per MPEP § 2106.05(g).
Thus, the way in which the additional elements use or interact with the judicial exception do not integrate the judicial exception into a practical application.
Step 2B: The additional elements from Step 2A Prong 2 include invoking generic computer components to apply the underlying judicial exception and insignificant extra-solution activity of data gathering recited by “extract one or more similar objects that exist within a predetermined number of hops from the prediction target object with reference to the graph” which are well-understood routine and conventional activities similar to presenting offers and gathering statistics per MPEP 2106.05(d)(II). Thus, the additional elements, viewed individually or in combination, do not provide an inventive concept or otherwise amount to significantly more than the abstract idea itself. See MPEP § 2106.05.
Claim 8
Step 1: A machine, as above.
Step 2A Prong 1: The claim recites the abstract ideas as the judicial exception of claim 1:
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The additional elements of the claim are as follows:
wherein in the acquisition process, the at least one processor is configured to carry out: These additional elements are recited at a high level of generality and amount to invoking computers or other machinery merely as a tool to apply the underlying judicial exception. See MPEP § 2106.05(f).
an acceptance process of accepting a sentence set: These additional elements amount to insignificant extra-solution activity in the form of mere data gathering per MPEP § 2106.05(g).
and an entity extraction process of extracting a plurality of entities from the sentence set: These additional elements amount to insignificant extra-solution activity in the form of mere data gathering per MPEP § 2106.05(g).
and the at least one processor is configured to acquire, as the set of objects, the plurality of entities that have been extracted in the entity extraction process or a combination of the plurality of entities that have been extracted in the entity extraction process and a sentence from which the plurality of entities are extracted: These additional elements amount to insignificant extra-solution activity in the form of selecting a particular data source or type of data to be manipulated per MPEP § 2106.05(g).
Thus, the way in which the additional elements use or interact with the judicial exception do not integrate the judicial exception into a practical application.
Step 2B: The additional elements from Step 2A Prong 2 include invoking generic computer components to apply the underlying judicial exception and insignificant extra-solution activity of data gathering recited by “an acceptance process of accepting a sentence set” which are well-understood routine and conventional activities similar to receiving or transmitting data over a network, “an entity extraction process of extracting a plurality of entities from the sentence set” which are well-understood routine and conventional activities similar to presenting offers and gathering statistics, and “the at least one processor is configured to acquire, as the set of objects, the plurality of entities that have been extracted in the entity extraction process or a combination of the plurality of entities that have been extracted in the entity extraction process and a sentence from which the plurality of entities are extracted” which are well-understood routine and conventional activities similar to receiving or transmitting data over a network per MPEP 2106.05(d)(II). Thus, the additional elements, viewed individually or in combination, do not provide an inventive concept or otherwise amount to significantly more than the abstract idea itself. See MPEP § 2106.05.
Claim 9
Step 1: A machine, as above.
Step 2A Prong 1: The claim recites the abstract ideas of claim 1, as well as inter alia:
an identity evaluation process of evaluating identity between the objects included in the set of objects and identifying, as the similar object, an object which is identical to the prediction target object: These limitations recite a mentally performable process with the aid of pen and paper of using observation and judgement to evaluate an identity between the objects included in the set of objects and identify, as the similar object, an object which is identical to the prediction target object.
Thus, the claim recites a judicial exception.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The additional elements of the claim are as follows:
wherein in the evaluation process, the at least one processor is configured to carry out: These additional elements are recited at a high level of generality and amount to invoking computers or other machinery merely as a tool to apply the underlying judicial exception. See MPEP § 2106.05(f).
Thus, the way in which the additional elements use or interact with the judicial exception do not integrate the judicial exception into a practical application.
Step 2B: The additional elements from Step 2A Prong 2 include invoking generic computer components to apply the underlying judicial exception. Thus, the additional elements, viewed individually or in combination, do not provide an inventive concept or otherwise amount to significantly more than the abstract idea itself. See MPEP § 2106.05.
Claim 10
Step 1: A machine, as above.
Step 2A Prong 1: The claim recites the abstract ideas as the judicial exception of claim 1:
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The additional elements of the claim are as follows:
wherein the at least one processor is configured to carry out a display process of displaying: the prediction target object; and at least one of the similar objects or at least one of the similar labels: These additional elements amount to insignificant extra-solution activity in the form of selecting a particular data source or type of data to be manipulated per MPEP § 2106.05(g).
Thus, the way in which the additional elements use or interact with the judicial exception do not integrate the judicial exception into a practical application.
Step 2B: The additional elements from Step 2A Prong 2 include invoking generic computer components to apply the underlying judicial exception and insignificant extra-solution activity of data gathering recited by “the at least one processor is configured to carry out a display process of displaying: the prediction target object; and at least one of the similar objects or at least one of the similar labels” which are well-understood routine and conventional activities similar to receiving or transmitting data over a network per MPEP 2106.05(d)(II). Thus, the additional elements, viewed individually or in combination, do not provide an inventive concept or otherwise amount to significantly more than the abstract idea itself. See MPEP § 2106.05.
Claim 11
Step 1: A machine, as above.
Step 2A Prong 1: The claim recites the abstract ideas as the judicial exception of claim 1:
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The additional elements of the claim are as follows:
wherein the at least one processor is configured to carry out a display process of displaying: a yet-to-be-modified label of the prediction target object or the label given to the prediction target object; and the similar label(s): These additional elements amount to insignificant extra-solution activity in the form of selecting a particular data source or type of data to be manipulated per MPEP § 2106.05(g).
Thus, the way in which the additional elements use or interact with the judicial exception do not integrate the judicial exception into a practical application.
Step 2B: The additional elements from Step 2A Prong 2 include invoking generic computer components to apply the underlying judicial exception and insignificant extra-solution activity of data gathering recited by “wherein the at least one processor is configured to carry out a display process of displaying: a yet-to-be-modified label of the prediction target object or the label given to the prediction target object; and the similar label(s)” which are well-understood routine and conventional activities similar to receiving or transmitting data over a network per MPEP 2106.05(d)(II). Thus, the additional elements, viewed individually or in combination, do not provide an inventive concept or otherwise amount to significantly more than the abstract idea itself. See MPEP § 2106.05.
Claim 12
Step 1: These claims are directed to “An information processing method comprising:”; therefore, it is directed the statutory category of a process.
Step 2A Prong 1: Claim 12 recites the same judicial exception as Claim 1.
Step 2A Prong 2: The judicial exception recited in these claims are not integrated into a practical application. The analysis at this step for Claim 12 mirrors that of Claim 1.
Step 2B: The additional elements from Step 2A Prong 2 do not contain significantly more than the judicial exception for these claims. The analysis at this step for Claim 12 mirrors that of Claim 1.
Claim 13
Step 1: This claim recites "A computer-readable non-transitory storage medium storing a program for causing a computer to function as an information processing apparatus, the program causing the computer to carry out"; therefore, it is directed to the statutory category of an article of manufacture.
Step 2A Prong 1: Claim 13 recite the same judicial exception as Claim 1.
Step 2A Prong 2: The judicial exception recited in these claims are not integrated into a practical application. The only difference between Claim 13 and Claim 1, is that Claim 13 is directed to "a computer-readable non-transitory storage medium storing a program for causing a computer to function as an information processing apparatus, the program causing the computer to carry out”. However, mere recitation that a judicial exception is to be performed using generic computer equipment in their ordinary capacity, i.e. a computer-readable non-transitory storage medium storing a program for causing a computer to function as an information processing apparatus, the program causing the computer to carry out, cannot meaningfully integrate the judicial exception into a practical application. See MPEP 2106.05(f). With that exception, the analysis at this step for Claim 13 mirrors that of Claim 1.
Step 2B: The additional elements from Step 2A Prong 2 do not contain significantly more than the judicial exception for these claims. The only difference between Claim 13 and Claim 1, is that Claim 13 is directed to "a computer-readable non-transitory storage medium storing a program for causing a computer to function as an information processing apparatus, the program causing the computer to carry out”. However, mere recitation that a judicial exception is to be performed using generic computer equipment in their ordinary capacity, i.e. a computer-readable non-transitory storage medium storing a program for causing a computer to function as an information processing apparatus, the program causing the computer to carry out, cannot amount to significantly more than the judicial exception. See MPEP 2106.05(f). With that exception, the analysis at this step for Claim 13 mirrors that of Claim 1.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-4, 7 & 12-13 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Pal et al. (US 10922609 B2, published 02/16/2021), hereafter Pal.
Regarding independent claim 1, Pal teaches a system comprising:
at least one processor, the at least one processor being configured to carry out ([Col. 23, Lines 49-50] discusses the use of a processor);
an acquisition process of acquiring a set of objects ([Col. 9, Lines 34-38] discusses acquiring a set of nodes wherein each node represents a user, representing an object);
an evaluation process of evaluating a degree of similarity between objects included in the set of objects and identifying one or a plurality of similar objects which are similar to a prediction target object ([Col. 4, Lines 27-35] discusses quantifying similarity between nodes in the set of nodes; [Col. 8, Lines 8-20] discusses identifying similar objects which are similar to a prediction target object);
and a prediction process of determining a label to be given to the prediction target object with reference to a similar label(s), the similar label(s) being a label(s) which is/are given to each of the one or a plurality of similar objects and which has/have been predicted by a prediction model ([Abstract & Col. 9, Lines 1-8] discusses the systems classifier, which acts as a prediction model, predicting labels for nodes, then determining the final label using the labels of neighbors, which constitute similar labels that are given to the plurality of similar objects, via propagation).
Regarding dependent claim 2, Pal teaches the claimed invention as claimed in claim 1, including wherein in the evaluation process, the at least one processor is configured to calculate a respective score(s) of the similar label(s), and in the prediction process, the at least one processor is configured to determine the label to be given to the prediction target object with further reference to the score(s) ([Col. 4-5, Lines 37-3; Col. 6, Lines 1-3; Col. 7, Lines 11-14] discusses computing a numeric score for each candidate label for each node and uses those scores to pick the final label).
Regarding dependent claim 3, Pal teaches the claimed invention as claimed in claim 1, including wherein in the prediction process, the at least one processor is configured to: predict a yet-to-be-modified label of the prediction target object with use of the prediction model; predict the similar label(s) with use of the prediction model; and determine, as the label to be given to the prediction target object, a modified label that is obtained by modifying the yet-to-be-modified label with reference to the similar label(s) ([Col. 6, Lines 5-30] discusses generating a yet-to-be-modified label for the target node using model q; model q simultaneously predicts labels for the target neighbors; then label distribution is modified and this modification is done with reference to neighboring/similar labels, with this process being repeated until convergence).
Regarding dependent claim 4, Pal teaches the claimed invention as claimed in claim 3, including wherein in the evaluation process, the at least one processor identifies a plurality of similar objects, and in the prediction process, the at least one processor is configured to: extract one or more similar labels from a plurality of similar labels given to the plurality of similar objects; and carry out a comparison between the extracted one or more similar labels and the yet-to-be-modified label to determine the modified label ([Col. 8, Lines 8-20] discusses identifying similar objects which are similar to a prediction target object; [Col. 4, Lines 50-67] discusses iteratively extracting propagated-label term “S F^(t)”, which is a similar label, and comparing it to Y, which is a yet-to-be-modified label to determine the modified label).
Regarding dependent claim 7, Pal teaches the claimed invention as claimed in claim 1, including wherein in the evaluation process, the at least one processor is configured to identify the one or more similar objects by outputting a graph representing a similarity relationship between the objects, and in the prediction process, the at least one processor is configured to: extract one or more similar objects that exist within a predetermined number of hops from the prediction target object with reference to the graph; and determine the label to be given to the prediction target object with reference to the similar label(s) given to the extracted one or more similar objects ([Col. 9, Lines 33-41] discusses a graph data structure that represents a similarity between objects, and these objects have a single degree of separation; [Col. 8, Lines 8-10] discusses the framework of a predetermined number of hops from the prediction target object with reference to the graph; [Col. 8, Lines 23-45] discusses the system will extract an object to determine the label to be given to the target object with reference to the labels given to the extracted objected).
Regarding claim 12, claim 12 is a method claim that is substantially the same as the system of claim 1. Therefore, claim 12 is rejected for the same reasons as claim 1.
Regarding claim 13, claim 13 is a non-transitory computer-readable storage medium claim that is substantially the same as the method of claim 1. Therefore, claim 13 is rejected for the same reasons as claim 1.
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.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Pal, as applied in claim 1, in view of Ravi et al. (US 9852231 B2, published 12/26/2017), hereafter Ravi.
Regarding dependent claim 5, Pal teaches the invention as claimed in claim 1, including:
the at least one processor is configured to ([Col. 23, Lines 49-50] discusses the use of a processor);
a prediction process of determining a label to be given to the prediction target object with reference to a similar label(s) ([Abstract & Col. 9, Lines 1-8] discusses the systems classifier, which acts as a prediction model, predicting labels for nodes, then determining the final label using the labels of neighbors, which constitute similar labels that are given to the plurality of similar objects, via propagation).
Pal does not explicitly teach to sort the plurality of similar labels given to the plurality of similar objects with reference to the plurality of similar labels given to the plurality of similar objects and the respective scores of the similar labels; sort a plurality of yet-to-be-modified labels related to the prediction target object with reference to the plurality of yet-to-be-modified labels related to the prediction target object and the respective scores of the yet-to-be-modified labels; and determine, as the modified labels, the yet-to-be-modified labels included in M (M is a natural number) top-ranked similar labels given to the plurality of similar objects among N (N is a natural number) top-ranked yet-to-be-modified labels related to the prediction target object.
However, in a similar field of endeavor, Ravi teaches a system for sorting similar labels with reference to their respective scores, sorting yet-to-be-modified labels related to the target object with reference to their respective scores, and determining the yet-to-be-modified labels in M top-ranked similar labels given to objects among N top-ranked labels related to the prediction target object ([Col. 12, Lines 55-63] discusses first sorting or ranking the plurality of labels with reference to the respective scores calculated for each similar label; [Col. 5, Lines 9-14] discusses sorting the yet-to-be-modified labels based on their scores; further, the structure tracks a list of top-ranked quantity k labels and determines the modified labels at the intersection of the top k yet-to-be-modified labels and the top k similar labels).
Because Pal teaches the use of a processor, and a prediction process of determining a label to be given to the prediction target object with reference to a similar label(s); and Ravi teaches sorting similar labels with reference to their respective scores, sorting yet-to-be-modified labels related to the target object with reference to their respective scores, and determining the yet-to-be-modified labels in M top-ranked similar labels given to objects among N top-ranked labels related to the prediction target object, accordingly, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to incorporate sorting similar labels with reference to their respective scores, sorting yet-to-be-modified labels related to the target object with reference to their respective scores, and determining the yet-to-be-modified labels in M top-ranked similar labels given to objects among N top-ranked labels related to the prediction target object as taught by Ravi into Pal’s system, with a reasonable expectation of success, to teach wherein in the prediction process, the at least one processor configured to: sort the plurality of similar labels given to the plurality of similar objects with reference to the plurality of similar labels given to the plurality of similar objects and the respective scores of the similar labels; sort a plurality of yet-to-be-modified labels related to the prediction target object with reference to the plurality of yet-to-be-modified labels related to the prediction target object and the respective scores of the yet-to-be-modified labels; and determine, as the modified labels, the yet-to-be-modified labels included in M (M is a natural number) top-ranked similar labels given to the plurality of similar objects among N (N is a natural number) top-ranked yet-to-be-modified labels related to the prediction target object. This combination would have been motivated by the desire to sort, categorize, and show the most likely or highest rated labels that could be assigned to a node, entity, or object (Ravi [Col. 5]).
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Pal, in view of Ravi, as applied in claim 5, and further in view of Wu et al. ("Probase: A Probabilistic Taxonomy for Text Understanding", 2012), hereafter Wu.
Wu was cited in the IDS submitted 04/22/2024.
Regarding dependent claim 6, the combination of Pal and Ravi teaches the invention as claimed in claim 5, including to determine, as the modified labels, the yet-to-be-modified labels included in M (M is a natural number) top-ranked similar labels given to the plurality of similar objects among N (N is a natural number) top-ranked yet-to-be-modified labels related to the prediction target object (Ravi [Col. 12, Lines 55-63] discusses first sorting or ranking the plurality of labels with reference to the respective scores calculated for each similar label; Ravi [Col. 5, Lines 9-14] discusses sorting the yet-to-be-modified labels based on their scores; further, the structure tracks a list of top-ranked quantity k labels and determines the modified labels at the intersection of the top k yet-to-be-modified labels and the top k similar labels).
The combination of Pal and Ravi does not explicitly teach to further sort the plurality of similar labels given to the plurality of similar objects with reference to a hierarchical relationship between the plurality of similar labels.
However, in a similar field of endeavor, Wu teaches a method of constructing a Probase to compare pairs based on a hierarchical relationship ([Sec. 3] discusses constructing a Taxonomy from pairs of edges where a reference to a hierarchical relationship between the labels is used to organize and sort pairs).
Because the combination of Pal and Ravi teaches determining the yet-to-be-modified labels in M top-ranked similar labels given to objects among N top-ranked labels related to the prediction target object; and Wu teaches a method of constructing a ‘Probase’ to compare pairs based on a hierarchical relationship, accordingly, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to incorporate a method of constructing a ‘Probase’ to compare pairs based on a hierarchical relationship as taught by Wu into the combination of Pal and Ravi’s system, with a reasonable expectation of success, to teach wherein in the prediction process, the at least one processor is configured to: further sort the plurality of similar labels given to the plurality of similar objects with reference to a hierarchical relationship between the plurality of similar labels; and determine, as the modified labels, the yet-to-be-modified labels included in M (M is a natural number) top-ranked similar labels given to the plurality of similar objects among N (N is a natural number) top-ranked yet-to-be-modified labels related to the prediction target object. This combination would have been motivated by the desire that fine level of understanding is desirable in many important tasks, such as named entity recognition (Wu [Sec. 1]).
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Pal, as applied in claim 1, in view of Abdel-Reheem et al. (US 9971763 B2, published 05/15/2018), hereafter Abdel-Reheem.
Regarding dependent claim 8, Pal teaches the invention as claimed in claim 1, including:
at least one processor, the at least one processor being configured to carry out ([Col. 23, Lines 49-50] discusses the use of a processor);
an acquisition process of acquiring a set of objects ([Col. 9, Lines 34-38] discusses acquiring a set of nodes wherein each node represents a user, representing an object).
Pal does not explicitly teach an acceptance process of accepting a sentence set; and an entity extraction process of extracting a plurality of entities from the sentence set, and the at least one processor is configured to acquire, as the set of objects, the plurality of entities that have been extracted in the entity extraction process or a combination of the plurality of entities that have been extracted in the entity extraction process and a sentence from which the plurality of entities are extracted.
However, in a similar field of endeavor, Abdel-Reheem teaches an acceptance process, an extraction process, and acquiring the entities that have been extracted along with their corresponding sentences ([Col. 2-3, Lines 65-4] discusses an entity extractor that accepts a sentence set with class labels, and a process that extracts text, or entities, from the sentence set; [Col. 4, Lines 54-62] discusses acquiring the entities that have been extracted either alone or in combination with its surrounding sentence or position within the corresponding sentence).
Because Pal teaches a processor and an acquisition process; and Abdel-Reheem teaches an acceptance process, an extraction process, and acquiring the entities that have been extracted along with their corresponding sentences, accordingly, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to incorporate an acceptance process, an extraction process, and acquiring the entities that have been extracted along with their corresponding sentences as taught by Abdel-Reheem into Pal’s system, with a reasonable expectation of success, to teach wherein in the acquisition process, the at least one processor is configured to carry out: an acceptance process of accepting a sentence set; and an entity extraction process of extracting a plurality of entities from the sentence set, and the at least one processor is configured to acquire, as the set of objects, the plurality of entities that have been extracted in the entity extraction process or a combination of the plurality of entities that have been extracted in the entity extraction process and a sentence from which the plurality of entities are extracted. This combination would have been motivated by the desire to scale up named entity recognition systems to recognize larger numbers of classes of named entity by implementing extracting from data input (Abdel-Reheem [Background]).
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Pal, as applied in claim 1, in view of Ledell Wu et al. ("Scalable Zero-shot Entity Linking with Dense Entity Retrieval", arXiv:1911.03814v3 [cs.CL] 29 Sep 2020), hereafter Ledell.
Ledell was cited in the IDS submitted 04/22/2024.
Regarding dependent claim 9, Pal teaches the invention as claimed in claim 1, including an evaluation process of evaluating a degree of similarity between objects included in the set of objects and identifying one or a plurality of similar objects which are similar to a prediction target object ([Col. 4, Lines 27-35] discusses quantifying similarity between nodes in the set of nodes; [Col. 8, Lines 8-20] discusses identifying similar objects which are similar to a prediction target object).
Pal does not explicitly teach an identity evaluation process of evaluating identity between the objects included in the set of objects and identifying, as the similar object, an object which is identical to the prediction target object.
However, in a similar field of endeavor, Ledell teaches an evaluation process in which entity candidates are compared to identify an identical object ([Sec. 4] discusses an evaluation process wherein an entity candidate is evaluated against other objects; and the network is trained to maximize the score of the correct entity; thus, the process identifies an object which is identical to the prediction target object).
Because Pal teaches an evaluation process; and Ledell teaches an evaluation process in which entity candidates are compared to identify an identical object, accordingly, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to incorporate an evaluation process in which entity candidates are compared to identify an identical object as taught by Ledell into Pal’s system, with a reasonable expectation of success, to teach wherein in the evaluation process, the at least one processor is configured to carry out an identity evaluation process of evaluating identity between the objects included in the set of objects and identifying, as the similar object, an object which is identical to the prediction target object. This combination would have been motivated by the desire to achieve very efficient linking with modest loss of accuracy (Ledell [Sec. 1]).
Claims 10-11 are rejected under 35 U.S.C. 103 as being unpatentable over Pal, as applied in claim 1, in view of Oki Motoyoshi et al. (JP 2020027540 A, published 02/20/2020), hereafter Oki.
Oki was cited in the IDS submitted 04/22/2024.
Regarding dependent claim 10, Pal teaches the invention as claimed in claim 1, including at least one processor ([Col. 23, Lines 49-50] discusses the use of a processor).
Pal does not explicitly teach to carry out a display process of displaying: the prediction target object; and at least one of the similar objects or at least one of the similar labels.
However, in a similar field of endeavor, Oki teaches a labeling method and program in which a display control unit displays a labeling screen comprising the prediction target object and one of the similar objects or similar labels ([Step S101] discusses displaying a target object with at least one of the similar objects).
Because Pal teaches the use of a processor; and Oki teaches a labeling method and program in which a display control unit displays a labeling screen comprising the prediction target object and one of the similar objects or similar labels, accordingly, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to incorporate a labeling method and program in which a display control unit displays a labeling screen comprising the prediction target object and one of the similar objects or similar labels as taught by Oki into Pal’s system, with a reasonable expectation of success, to teach wherein the at least one processor is configured to carry out a display process of displaying: the prediction target object; and at least one of the similar objects or at least one of the similar labels. This combination would have been motivated by the desire to display the results of the display process and comprise a method of storing the information in a storage unit (Oki [Unit 10]).
Regarding dependent claim 11, Pal teaches the invention as claimed in claim 1, including at least one processor ([Col. 23, Lines 49-50] discusses the use of a processor).
Pal does not explicitly teach to carry out a display process of displaying: a yet-to-be-modified label of the prediction target object or the label given to the prediction target object; and the similar label(s).
However, in a similar field of endeavor, Oki teaches a labeling method and program in which a display control unit displays at least two categories of values relating to the labeling process ([Step S101] discusses displaying a target object with at least one of the similar objects).
Because Pal teaches the use of a processor; and Oki teaches a labeling method and program in which a display control unit displays at least two categories of values relating to the labeling process, accordingly, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to incorporate a labeling method and program in which a display control unit displays at least two categories of values relating to the labeling process as taught by Oki into Pal’s system, with a reasonable expectation of success, to teach wherein the at least one processor is configured to carry out a display process of displaying. This combination would have been motivated by the desire to display the results of the display process and comprise a method of storing the information in a storage unit (Oki [Unit 10]).
The combination of Pal and Oki does not explicitly teach the display comprising a yet-to-be-modified label of the prediction target object or the label given to the prediction target object; and the similar label(s).
However, the combination of Pal and Oki teaches displaying at least two categories of values comprising the prediction target object, and at least one of the similar objects or at least one of the similar labels ([Step S101] discusses displaying a target object with at least one of the similar objects), which according to broadest reasonable interpretation, are simply design choices. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have implemented the display process of displaying at least two categories of values relating to the labeling process with a yet-to-be-modified label of the prediction target object or the label given to the prediction target object; and the similar label(s) in order to execute the display process as recited in claim 11.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Alexander Ratner et al. ("Snorkel: Rapid training data creation with weak supervision," Proceedings of the VLDB Endowment, International Conference on Very Large Data Bases, Vol. 11, No. 3, NIH Public Access, 2017) ([Abstract] Labeling training data is increasingly the largest bottleneck in deploying machine learning systems. We present Snorkel, a first-of-its-kind system that enables users to train state of-the-art models without hand labeling any training data. Instead, users write labeling functions that express arbitrary heuristics, which can have unknown accuracies and correlations. Snorkel denoises their outputs without access to ground truth by incorporating the first end-to-end implementation of our recently proposed machine learning paradigm, data programming. We present a flexible interface layer for writing labeling functions based on our experience over the past year collaborating with companies, agencies, and research labs)
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/RILEY S ACOSTA/Examiner, Art Unit 2143
/JENNIFER N WELCH/Supervisory Patent Examiner, Art Unit 2143
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