DETAILED ACTION
Status of Claims
This Office action is responsive to communications filed on 2025-08-08. Claim(s) 2-6, 8, 13 were cancelled. Claim(s) 23-26 were added. Claim(s) 1, 7, 9-12, and 14-26 is/are pending and are examined herein.
Claim(s) 1, 7, 9-12, and 14-26 is/are objected to.
Claim(s) 10 is/are rejected under 35 USC 112(d).
Claim(s) 7, 9, 11-12, and 18 is/are rejected under 35 USC 112(b).
Claim(s) 7 is/are rejected under 35 USC 112(a).
Claim(s) 1, 7, 9-12, and 14-26 is/are rejected under 35 USC 101.
Claim(s) 1, 7, 9, 11-12, and 21-22 is/are rejected under 35 USC 102.
Claim(s) 10 and 14-26 is/are rejected under 35 USC 103.
Notice of Pre-AIA or AIA Status
The present application, filed on or after 2013-03-16, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The attached information disclosure statement(s) (IDS), submitted on 2025-05-08, is/are in compliance with the provisions of 37 CFR 1.97. Accordingly, the attached information disclosure statement(s) is/are being considered by the examiner.
Response to Arguments
Regarding objections for informalities and rejections under 35 USC 112, the applicant’s amendments resolve concerns discussed previously but also raise new concerns. Concerns about the pending claims are described below.
Regarding rejections under 35 USC 101, the applicant’s arguments have been fully considered but they are unpersuasive:
The applicant asserts that various operations “cannot be reasonably performed mentally and require computer implementation” [remarks, page 18] but the examiner disagrees. None of the limitations in the claim are recited narrowly enough so as to require computer implementation.
The applicant attempts various arguments attempting to argue that the claims provide integrate the abstract ideas into a practical application by providing an improvement [remarks, pages 18-20] (e.g. “[t]he interplay between grouping, model structure, and evaluation defines a technical improvement in model selection workflows” [remarks, page 18], “[t]he steps form a coherent technical solution to an optimization problem in predictive modeling” [remarks, page 18] or “[these claims] implement a sequence of technically meaningful processes to optimize model structure based on model data” [remarks, page 18], “the present claims as a whole provide an improvement to this technological environment” [remarks, page 20]). However, MPEP 2106.05(a) indicates that one of the requirements of the improvements analysis is that a “judicial exception alone cannot provide the improvement”. In the present case, every limitation of the independent claims (possibly except for recitations of generic computing equipment and of obtaining data on which to operate) is an abstract idea, so any purported improvements would necessarily be provided by judicial exceptions. Consequently, the invention as claimed does not meet the requirements of the improvements analysis.
The complete 101 analysis, updated in view of the applicant’s amendments, is given below.
Regarding rejections under 35 USC 102/103 of the originally filed claims, the applicant “traverses this ground of rejection” [remarks, page 20] but provides no rationale in support of this traversal. This bare assertion of traversal fails to comply with 37 CFR 1.111(b) because it amounts to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the originally filed claims patentably distinguishes them from the references. Regarding the amended claims, the applicant’s remarks have been fully considered but they are unpersuasive:
Regarding claim 1, the applicant argues that “[c]laim 1 introduces specific time-based grouping” and that “Mavrovouniotis… does not disclose these operations, especially in the context of time-indexed variable grouping” [remarks, page 21]. However, Mavrovouniotis clearly discloses time-based grouping of time-indexed variables [Mavrovouniotis, sections 2.2-2.3]. The applicant also argues that “[c]laim 1 also now incorporates the contents of cancelled claims 2-4 and 8” [remarks, page 21] but the examiner disagrees with this characterization of amended claim 1. Cancelled claims 2-4 recited limitations regarding applying groupings based on evaluation values, whereas limitations recited in amended claim 1 are about selecting architectures based on evaluation values. The latter is disclosed in Mavrovouniotis. The examiner maintains that claim 1 as amended is disclosed by Mavrovouniotis alone.
Regarding claim 14, the applicant asserts that the calculation of cross-correlation is not disclosed by Mavrovouniotis [remarks, page 21] while also admitting that “Tran discloses the use of correlation” [remarks, page 21]. This means that the “integrated pipeline in claim 14” [remarks, page 14] is in fact disclosed by Mavrovouniotis in view of Tran. The applicant's remarks do not comply with 37 CFR 1.111(c) because they do not clearly point out the patentable novelty which they think the claims present in view of the state of the art disclosed by the references cited. Further, they do not show how the amendments avoid such references.
Regarding claim 10, the applicant’s remarks [remarks, page 22] do not comply with 37 CFR 1.111(c) because they do not clearly point out the patentable novelty which they think the claims present in view of the state of the art disclosed by the references cited. Further, they do not show how the amendments avoid such references.
Regarding claim 16, the applicant asserts that “Lin discusses coefficient-based pruning but not its integration into group-based model generation and architecture selection” [remarks, page 22] but these features are disclosed by Mavrovouniotis in view of Lin. The applicant's remarks do not comply with 37 CFR 1.111(c) because they do not clearly point out the patentable novelty which they think the claims present in view of the state of the art disclosed by the references cited. Further, they do not show how the amendments avoid such references. The applicant also asserts that the claimed invention “includes dynamic candidate evaluation and selection mechanisms that are not trivially combinable” [remarks, page 22]. This remark does not appear relevant to the rejection as given since both evaluation and selection of model architecture candidates are disclosed by Mavrovouniotis alone; no combination of references is required for disclosing the combination of these two features.
The complete prior art mapping, updated in view of the applicant’s amendments, is given below.
Examiner’s Remarks
Claims are grouped as follows in this Office action:
Claim Group A: Claims 1, 21-22, and Dependents (7, 9, 11-12)
Claim Group B: Claims 14, 23-24, and Dependents (10, 15)
Claim Group C: Claims 16, 25-26, and Dependents (17-20)
Claim Objections
Claim(s) 1, 7, 9, 11-12 is/are objected to because of the following informalities:
Claim Group A
Claims 1 and 21-22 recite the plurality of candidates but this should be “the plurality of model architecture candidates” for consistency of nomenclature and proper antecedent basis. Dependent claims 7, 9, and 11-12 inherit the objection.
Claim 12 recites according to claim 1, the prediction model but this is ungrammatical; it should be “according to claim 1, wherein the prediction model”.
Claim Group B
Claims 14 and 23-24 recite the evaluation value corresponding to each combination of the grouping candidates and the model architecture candidates [emphasis added] but this should be “the evaluation values values of the prediction models
Claim Group C
Claims 16 and 25-26 recite the evaluation value corresponding to each combination of the grouping candidates and the model architecture candidates [emphasis added] but this should be “the evaluation values values of the prediction models
Claim 19 recites when the value of the second variable corresponding to a peak portion [emphasis added] but this should be “when the value of the second variable corresponds to a peak portion” for grammaticality.
Appropriate correction is required.
Claim Rejections - 35 USC 112(d)
The following is a quotation of 35 USC 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 USC 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claim(s) 10 is/are rejected under 35 USC 112(d) or pre-AIA 35 USC 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends.
Claim Group B
Dependent claim 10 includes a reference to independent claim 14, but this is not a “a reference to a claim previously set forth” [emphasis added] as required by 35 USC 112(d). MPEP 608.01(n)(III) indicates that, “[a]lthough the requirements of 35 USC 112(d) are related to matters of form, non-compliance with 35 USC 112(d) renders the claim unpatentable just as non-compliance with other paragraphs of 35 USC 112 would” and that “[c]laims which are in improper dependent form for failing to further limit the subject matter of a previous claim… should be rejected under 35 USC 112(d)”. Consequently, claim 10 is rejected for being an improper dependent of claim 14.
Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
Claim Rejections - 35 USC 112(b)
The following is a quotation of 35 USC 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 USC 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim(s) 7, 9, 11-12, and 18 is/are rejected under 35 USC 112(b) or 35 USC 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 USC 112, the applicant), regards as the invention.
Claim Group A
Claim 7 recites and the automatic generation method is configured to generate the grouping candidates by dividing the arranged plurality of first variables at different positions, and generate a plurality of grouping candidates by repeatedly changing the division positions [emphasis added] but the underlined phrases lack antecedent basis. Regarding the first phrase, the examiner suggests simply deleting the phrase “and the automatic generation method is configured to”. The scope of the remainder of this limitation is not clear to the examiner even in view of the specification (cf. 112(a) rejections). The applicant is advised to use alternate language which clearly lays out the scope of the claim and which is consistent with language used in the specification.
Claims 9 and 11-12 recite the prediction model but this has ambiguous antecedent basis since the parent claim recites a plurality of prediction models, one for each of the plurality of model architecture candidates. For the purpose of compact prosecution, the claims are interpreted broadly as encompassing any one of these prediction models.
Claim Group C
Claim 18 recites based on a generic algorithm but this phrase is syntactically ambiguous: it is unclear whether it is the generation of first variables which is “based on a genetic algorithm” or the combining of explanatory variables which is “based on a genetic algorithm” or something else. For the purpose of compact prosecution, the claim is interpreted broadly as encompassing any of these interpretations.
Claim Rejections - 35 USC 112(a)
The following is a quotation of the first paragraph of 35 USC 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 USC 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claim(s) 7 is/are rejected under 35 USC 112(a) or 35 USC 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 USC 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim Group A
Claim 7 recites generate the grouping candidates by dividing the arranged plurality of first variables at different positions, and generate a plurality of grouping candidates by repeatedly changing the division positions but this feature is new matter as it is not described in the originally filed specification. The specification does not, for example, describe a process of “repeatedly changing the division positions” in chronologically arranged data. MPEP 2161.01 indicates that a computer-implemented functional claim limitation may lack adequate written description when the claims define the invention in functional language specifying a desired result but the specification does not sufficiently describe how the function is performed or the result is achieved. In other words, the algorithm or steps/procedure taken to perform the function must be described with sufficient detail so that one of ordinary skill in the art would understand how the inventor intended the function to be performed. Consequently, this limitation is new matter and is rejected for inadequate written description.
Claim Rejections - 35 USC 101
35 USC 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(s) 1, 7, 9-12, and 14-26 is/are rejected under 35 USC 101 because the claimed invention(s) is/are directed to abstract ideas without significantly more.
Claim Group A
Step 1. Claims 1, 7, 9, 11-12, and 22 fall under the statutory category of machines. Claim 21 falls under the statutory category of methods. An analysis of step 2 for each of these claims follows.
Claim 1
Step 2A Prong 1. The claim recites the following abstract ideas:
identify, among the plurality of first variables, a variable corresponding to a first time, a variable corresponding to a second time before the first time, and a variable corresponding to a third time after the first time; (This recites a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can identify variables corresponding to various times. See MPEP 2106.04(a)(2)(III).)
classify the variable corresponding to the first time into a first group, classify the variable corresponding to the second time into a second group, and classify the variable corresponding to the third time into a third group, thereby grouping the plurality of first variables into a plurality of groups and generating the plurality of groups including the first variables; (This recites a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can classify variables into groups. See MPEP 2106.04(a)(2)(III).)
generate, for each of a plurality of model architecture candidates, a prediction model configured to associate the first variables included in the first, second, and third groups with a predicted value of the second variable; (This recites a mathematical concept and a mental process that can be performed in the human mind or by a human using pen and paper. The examiner notes that the scope of the “prediction model” of the claim encompasses models such as linear regression [specification, 0034], which are mathematical concepts that are feasible to train/generate by a human mind. See MPEP 2106.04(a)(2)(I, III).)
calculate an evaluation value of each of the prediction models based on a difference between the predicted value of the second variable and a value of the second variable in the first data; (This recites a mathematical concept and a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can calculate values based on differences between a prediction and an actual value. See MPEP 2106.04(a)(2)(I, III).)
and determine, based on the evaluation values, a model architecture to be used from among the plurality of candidates. (This recites a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can determine/select an architecture to be used. See MPEP 2106.04(a)(2)(III).)
Step 2A Prong 2. The claim recites the following additional elements which, considered individually and as an ordered combination, do not integrate the abstract idea into a practical application:
An information processing apparatus, comprising: processing circuitry configured to (This recites generic computing components for performing an abstract idea. See MPEP 2106.05(f)(2).)
obtain first data including a plurality of first variables and a second variable; (This recites insignificant extra-solution activity. See MPEP 2106.05(g).)
Step 2B. The claim recites the following additional elements which, considered individually and as an ordered combination, do not amount to significantly more than the abstract idea:
An information processing apparatus, comprising: processing circuitry configured to (This recites generic computing components for performing an abstract idea. See MPEP 2106.05(f)(2).)
obtain first data including a plurality of first variables and a second variable; (This insignificant extra-solution activity is well-understood, routine, conventional as it is mere data transfer. See MPEP 2106.05(d)(II), “Receiving or transmitting data over a network” and/or “Storing and retrieving information in memory”.)
Claim 7
Step 2A Prong 1. The claim recites the following abstract ideas:
The abstract idea(s) in the parent claim(s).
[The information processing apparatus according to claim 1, wherein the processing circuitry is configured to] arrange the plurality of first variables in chronological order based on the times corresponding to the plurality of first variables, (This recites a mental process that can be performed in the human mind or by a human using pen and paper. See MPEP 2106.04(a)(2)(III).)
[and the automatic generation method is configured to] generate the grouping candidates by dividing the arranged plurality of first variables at different positions, and generate a plurality of grouping candidates by repeatedly changing the division positions. (This recites a mental process that can be performed in the human mind or by a human using pen and paper. See MPEP 2106.04(a)(2)(III).)
Step 2A Prong 2. The claim recites the following additional elements which, considered individually and as an ordered combination, do not integrate the abstract idea into a practical application:
The additional element(s) in the parent claim(s).
Step 2B. The claim recites the following additional elements which, considered individually and as an ordered combination, do not amount to significantly more than the abstract idea:
The additional element(s) in the parent claim(s).
Claim 9
Step 2A Prong 1. The claim recites the following abstract ideas:
The abstract idea(s) in the parent claim(s).
Step 2A Prong 2. The claim recites the following additional elements which, considered individually and as an ordered combination, do not integrate the abstract idea into a practical application:
The additional element(s) in the parent claim(s).
[The information processing apparatus according to claim 1, wherein] the first time corresponds to a time at when prediction is performed by the prediction model. (This recites data of a particular type or source, merely linking an abstract idea to a particular field of use. See MPEP 2106.05(h).)
Step 2B. The claim recites the following additional elements which, considered individually and as an ordered combination, do not amount to significantly more than the abstract idea:
The additional element(s) in the parent claim(s).
[The information processing apparatus according to claim 1, wherein] the first time corresponds to a time at when prediction is performed by the prediction model. (This recites data of a particular type or source, merely linking an abstract idea to a particular field of use. See MPEP 2106.05(h).)
Claim 11
Step 2A Prong 1. The claim recites the following abstract ideas:
The abstract idea(s) in the parent claim(s).
Step 2A Prong 2. The claim recites the following additional elements which, considered individually and as an ordered combination, do not integrate the abstract idea into a practical application:
The additional element(s) in the parent claim(s).
[The information processing apparatus according to claim 1, wherein] the prediction model is a neural network that includes an input layer, at least one intermediate layer, and an output layer, and the plurality of model architecture candidates differ in a number of nodes in the at least one intermediate layer. (This recites generic structure of neural networks. In other words, this recites merely applying (or equivalent) an abstract idea, or implementing an abstract idea on a computer, or using a computer as a tool to perform an abstract idea. See MPEP 2106.05(f).)
Step 2B. The claim recites the following additional elements which, considered individually and as an ordered combination, do not amount to significantly more than the abstract idea:
The additional element(s) in the parent claim(s).
[The information processing apparatus according to claim 1, wherein] the prediction model is a neural network that includes an input layer, at least one intermediate layer, and an output layer, and the plurality of model architecture candidates differ in a number of nodes in the at least one intermediate layer. (This recites generic structure of neural networks. In other words, this recites merely applying (or equivalent) an abstract idea, or implementing an abstract idea on a computer, or using a computer as a tool to perform an abstract idea. See MPEP 2106.05(f).)
Claim 12
Step 2A Prong 1. The claim recites the following abstract ideas:
The abstract idea(s) in the parent claim(s).
Step 2A Prong 2. The claim recites the following additional elements which, considered individually and as an ordered combination, do not integrate the abstract idea into a practical application:
The additional element(s) in the parent claim(s).
[The information processing apparatus according to claim 1,] the prediction model is a neural network that includes an input layer, at least one intermediate layer, and an output layer, and the plurality of model architecture candidates differ in a number of nodes in the at least one intermediate layer. (This recites generic structure of neural networks. In other words, this recites merely applying (or equivalent) an abstract idea, or implementing an abstract idea on a computer, or using a computer as a tool to perform an abstract idea. See MPEP 2106.05(f).)
Step 2B. The claim recites the following additional elements which, considered individually and as an ordered combination, do not amount to significantly more than the abstract idea:
The additional element(s) in the parent claim(s).
[The information processing apparatus according to claim 1,] the prediction model is a neural network that includes an input layer, at least one intermediate layer, and an output layer, and the plurality of model architecture candidates differ in a number of nodes in the at least one intermediate layer. (This recites generic structure of neural networks. In other words, this recites merely applying (or equivalent) an abstract idea, or implementing an abstract idea on a computer, or using a computer as a tool to perform an abstract idea. See MPEP 2106.05(f).)
Claim 21
Step 2A Prong 1. The claim recites the following abstract ideas:
identifying, among the plurality of first variables, a variable corresponding to a first time, a variable corresponding to a second time before the first time, and a variable corresponding to a third time after the first time; (This recites a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can identify variables corresponding to various times. See MPEP 2106.04(a)(2)(III).)
classifying the variable corresponding to the first time into a first group, classify the variable corresponding to the second time into a second group, and classify the variable corresponding to the third time into a third group, thereby grouping the plurality of first variables into a plurality of groups and generating the plurality of groups including the first variables; (This recites a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can classify variables into groups. See MPEP 2106.04(a)(2)(III).)
generating, for each of a plurality of model architecture candidates, a prediction model configured to associate the first variables included in the first, second, and third groups with a predicted value of the second variable; (This recites a mathematical concept and a mental process that can be performed in the human mind or by a human using pen and paper. The examiner notes that the scope of the “prediction model” of the claim encompasses models such as linear regression [specification, 0034], which are mathematical concepts that are feasible to train/generate by a human mind. See MPEP 2106.04(a)(2)(I, III).)
calculating an evaluation value of each of the prediction models based on a difference between the predicted value of the second variable and a value of the second variable in the first data; (This recites a mathematical concept and a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can calculate values based on differences between a prediction and an actual value. See MPEP 2106.04(a)(2)(I, III).)
and determining, based on the evaluation values, a model architecture to be used from among the plurality of candidates. (This recites a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can determine/select an architecture to be used. See MPEP 2106.04(a)(2)(III).)
Step 2A Prong 2. The claim recites the following additional elements which, considered individually and as an ordered combination, do not integrate the abstract idea into a practical application:
An information processing method, comprising: obtaining first data including a plurality of first variables and a second variable; (This recites insignificant extra-solution activity. See MPEP 2106.05(g).)
Step 2B. The claim recites the following additional elements which, considered individually and as an ordered combination, do not amount to significantly more than the abstract idea:
An information processing method, comprising: obtaining first data including a plurality of first variables and a second variable; (This insignificant extra-solution activity is well-understood, routine, conventional as it is mere data transfer. See MPEP 2106.05(d)(II), “Receiving or transmitting data over a network” and/or “Storing and retrieving information in memory”.)
Claim 22
Step 2A Prong 1. The claim recites the following abstract ideas:
identifying, among the plurality of first variables, a variable corresponding to a first time, a variable corresponding to a second time before the first time, and a variable corresponding to a third time after the first time; (This recites a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can identify variables corresponding to various times. See MPEP 2106.04(a)(2)(III).)
classifying the variable corresponding to the first time into a first group, classify the variable corresponding to the second time into a second group, and classify the variable corresponding to the third time into a third group, thereby grouping the plurality of first variables into a plurality of groups and generating the plurality of groups including the first variables; (This recites a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can classify variables into groups. See MPEP 2106.04(a)(2)(III).)
generating, for each of a plurality of model architecture candidates, a prediction model configured to associate the first variables included in the first, second, and third groups with a predicted value of the second variable; (This recites a mathematical concept and a mental process that can be performed in the human mind or by a human using pen and paper. The examiner notes that the scope of the “prediction model” of the claim encompasses models such as linear regression [specification, 0034], which are mathematical concepts that are feasible to train/generate by a human mind. See MPEP 2106.04(a)(2)(I, III).)
calculating an evaluation value of each of the prediction models based on a difference between the predicted value of the second variable and a value of the second variable in the first data; (This recites a mathematical concept and a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can calculate values based on differences between a prediction and an actual value. See MPEP 2106.04(a)(2)(I, III).)
and determining, based on the evaluation values, a model architecture to be used from among the plurality of candidates. (This recites a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can determine/select an architecture to be used. See MPEP 2106.04(a)(2)(III).)
Step 2A Prong 2. The claim recites the following additional elements which, considered individually and as an ordered combination, do not integrate the abstract idea into a practical application:
A non-transitory computer-readable medium having a computer program stored therein which causes a computer to perform processes, comprising: (This recites generic computing components for performing an abstract idea. See MPEP 2106.05(f)(2).)
obtaining first data including a plurality of first variables and a second variable; (This recites insignificant extra-solution activity. See MPEP 2106.05(g).)
Step 2B. The claim recites the following additional elements which, considered individually and as an ordered combination, do not amount to significantly more than the abstract idea:
A non-transitory computer-readable medium having a computer program stored therein which causes a computer to perform processes, comprising: (This recites generic computing components for performing an abstract idea. See MPEP 2106.05(f)(2).)
obtaining first data including a plurality of first variables and a second variable; (This insignificant extra-solution activity is well-understood, routine, conventional as it is mere data transfer. See MPEP 2106.05(d)(II), “Receiving or transmitting data over a network” and/or “Storing and retrieving information in memory”.)
Claim Group B
Step 1. Claims 14, 10, 15, and 24 fall under the statutory category of machines. Claim 23 falls under the statutory category of methods. An analysis of step 2 for each of these claims follows.
Claim 14
Step 2A Prong 1. The claim recites the following abstract ideas:
calculate a cross-correlation between a plurality of explanatory variables and an objective variable, based on time-series data of the explanatory variables and time-series data of the objective variable; (This recites a mathematical concept and/or a mental process that can be performed in the human mind or by a human using pen and paper. Cross-correlation is a mathematical concept, and its calculation can be performed by a human mind. See MPEP 2106.04(a)(2)(I, III).)
create first data including a plurality of first variables corresponding to a plurality of times before a prediction target time, selected from the plurality of explanatory variables based on the cross-correlation, and a second variable that includes the objective variable corresponding to the prediction target time; (This recites a mental process that can be performed in the human mind or by a human using pen and paper. See MPEP 2106.04(a)(2)(III).)
generate one or more grouping candidates by dividing the plurality of first variables in the first data into a plurality of groups using a predefined automatic generation method or a grouping method specified by a user; (This recites a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can generate grouping candidates. See MPEP 2106.04(a)(2)(III).)
generate, for each combination of the grouping candidates and one or more model architecture candidates, a prediction model configured to associate the first variables included in the respective groups with a predicted value of the second variable; (This recites a mathematical concept and a mental process that can be performed in the human mind or by a human using pen and paper. The examiner notes that the scope of the “prediction model” of the claim encompasses models such as linear regression [specification, 0034], which are mathematical concepts that are feasible to train/generate by a human mind. See MPEP 2106.04(a)(2)(I, III).)
calculate an evaluation value for each prediction model based on a difference between the predicted value of the second variable and a value of the second variable in the first data; (This recites a mathematical concept and a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can calculate values based on differences between a prediction and an actual value. See MPEP 2106.04(a)(2)(I, III).)
and determine a grouping and a model architecture to be used, based on the evaluation value corresponding to each combination of the grouping candidates and the model architecture candidates. (This recites a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can determine/select a grouping and/or architecture to be used based on their performance. See MPEP 2106.04(a)(2)(III).)
Step 2A Prong 2. The claim recites the following additional elements which, considered individually and as an ordered combination, do not integrate the abstract idea into a practical application:
An information processing apparatus, comprising: processing circuitry configured to: (This recites generic computing components for performing an abstract idea. See MPEP 2106.05(f)(2).)
Step 2B. The claim recites the following additional elements which, considered individually and as an ordered combination, do not amount to significantly more than the abstract idea:
An information processing apparatus, comprising: processing circuitry configured to: (This recites generic computing components for performing an abstract idea. See MPEP 2106.05(f)(2).)
Claim 10
Step 2A Prong 1. The claim recites the following abstract ideas:
The abstract idea(s) in the parent claim(s).
[The information processing apparatus according to claim 14, wherein the processing circuitry is configured to] generate the plurality of grouping candidates by randomly assigning the plurality of first variables to a plurality of groups. (This recites a mental process that can be performed in the human mind or by a human using pen and paper. See MPEP 2106.04(a)(2)(III).)
Step 2A Prong 2. The claim recites the following additional elements which, considered individually and as an ordered combination, do not integrate the abstract idea into a practical application:
The additional element(s) in the parent claim(s).
Step 2B. The claim recites the following additional elements which, considered individually and as an ordered combination, do not amount to significantly more than the abstract idea:
The additional element(s) in the parent claim(s).
Claim 15
Step 2A Prong 1. The claim recites the following abstract ideas:
The abstract idea(s) in the parent claim(s).
[The information processing apparatus according to claim 14, wherein the processing circuitry is configured to] calculate an autocorrelation of the objective variable, (This recites a mathematical concept and a mental process that can be performed in the human mind or by a human using pen and paper. Autocorrelation is a mathematical concept, and its calculation can be performed by a human mind. See MPEP 2106.04(a)(2)(I, III).)
and to include, as one of the first variables, the objective variable corresponding to a time before the prediction target time, based on the autocorrelation. (This recites a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can include variables in a data set. See MPEP 2106.04(a)(2)(III).)
Step 2A Prong 2. The claim recites the following additional elements which, considered individually and as an ordered combination, do not integrate the abstract idea into a practical application:
The additional element(s) in the parent claim(s).
Step 2B. The claim recites the following additional elements which, considered individually and as an ordered combination, do not amount to significantly more than the abstract idea:
The additional element(s) in the parent claim(s).
Claim 23
Step 2A Prong 1. The claim recites the following abstract ideas:
An information processing method, comprising: calculating a cross-correlation between a plurality of explanatory variables and an objective variable, based on time-series data of the explanatory variables and time-series data of the objective variable; (This recites a mathematical concept and/or a mental process that can be performed in the human mind or by a human using pen and paper. Cross-correlation is a mathematical concept, and its calculation can be performed by a human mind. See MPEP 2106.04(a)(2)(I, III).)
creating first data including a plurality of first variables corresponding to a plurality of times before a prediction target time, selected from the plurality of explanatory variables based on the cross-correlation, and a second variable that includes the objective variable corresponding to the prediction target time; (This recites a mental process that can be performed in the human mind or by a human using pen and paper. See MPEP 2106.04(a)(2)(III).)
generating one or more grouping candidates by dividing the plurality of first variables in the first data into a plurality of groups using a predefined automatic generation method or a grouping method specified by a user; (This recites a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can generate grouping candidates. See MPEP 2106.04(a)(2)(III).)
generating, for each combination of the grouping candidates and one or more model architecture candidates, a prediction model configured to associate the first variables included in the respective groups with a predicted value of the second variable; (This recites a mathematical concept and a mental process that can be performed in the human mind or by a human using pen and paper. The examiner notes that the scope of the “prediction model” of the claim encompasses models such as linear regression [specification, 0034], which are mathematical concepts that are feasible to train/generate by a human mind. See MPEP 2106.04(a)(2)(I, III).)
calculating an evaluation value for each prediction model based on a difference between the predicted value of the second variable and a value of the second variable in the first data; (This recites a mathematical concept and a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can calculate values based on differences between a prediction and an actual value. See MPEP 2106.04(a)(2)(I, III).)
and determining a grouping and a model architecture to be used, based on the evaluation value corresponding to each combination of the grouping candidates and the model architecture candidates. (This recites a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can determine/select a grouping and/or architecture to be used based on their performance. See MPEP 2106.04(a)(2)(III).)
Step 2A Prong 2. The claim recites the following additional elements which, considered individually and as an ordered combination, do not integrate the abstract idea into a practical application:
None.
Step 2B. The claim recites the following additional elements which, considered individually and as an ordered combination, do not amount to significantly more than the abstract idea:
None.
Claim 24
Step 2A Prong 1. The claim recites the following abstract ideas:
calculating a cross-correlation between a plurality of explanatory variables and an objective variable, based on time-series data of the explanatory variables and time-series data of the objective variable; (This recites a mathematical concept and/or a mental process that can be performed in the human mind or by a human using pen and paper. Cross-correlation is a mathematical concept, and its calculation can be performed by a human mind. See MPEP 2106.04(a)(2)(I, III).)
creating first data including a plurality of first variables corresponding to a plurality of times before a prediction target time, selected from the plurality of explanatory variables based on the cross-correlation, and a second variable that includes the objective variable corresponding to the prediction target time; (This recites a mental process that can be performed in the human mind or by a human using pen and paper. See MPEP 2106.04(a)(2)(III).)
generating one or more grouping candidates by dividing the plurality of first variables in the first data into a plurality of groups using a predefined automatic generation method or a grouping method specified by a user; (This recites a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can generate grouping candidates. See MPEP 2106.04(a)(2)(III).)
generating, for each combination of the grouping candidates and one or more model architecture candidates, a prediction model configured to associate the first variables included in the respective groups with a predicted value of the second variable; (This recites a mathematical concept and a mental process that can be performed in the human mind or by a human using pen and paper. The examiner notes that the scope of the “prediction model” of the claim encompasses models such as linear regression [specification, 0034], which are mathematical concepts that are feasible to train/generate by a human mind. See MPEP 2106.04(a)(2)(I, III).)
calculating an evaluation value for each prediction model based on a difference between the predicted value of the second variable and a value of the second variable in the first data; (This recites a mathematical concept and a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can calculate values based on differences between a prediction and an actual value. See MPEP 2106.04(a)(2)(I, III).)
and determining a grouping and a model architecture to be used, based on the evaluation value corresponding to each combination of the grouping candidates and the model architecture candidates. (This recites a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can determine/select a grouping and/or architecture to be used based on their performance. See MPEP 2106.04(a)(2)(III).)
Step 2A Prong 2. The claim recites the following additional elements which, considered individually and as an ordered combination, do not integrate the abstract idea into a practical application:
A non-transitory computer-readable medium having a computer program stored therein which causes a computer to perform processes, comprising: (This recites generic computing components for performing an abstract idea. See MPEP 2106.05(f)(2).)
Step 2B. The claim recites the following additional elements which, considered individually and as an ordered combination, do not amount to significantly more than the abstract idea:
A non-transitory computer-readable medium having a computer program stored therein which causes a computer to perform processes, comprising: (This recites generic computing components for performing an abstract idea. See MPEP 2106.05(f)(2).)
Claim Group C
Step 1. Claims 16-20 and 26 fall under the statutory category of machines. Claim 25 falls under the statutory category of methods. An analysis of step 2 for each of these claims follows.
Claim 16
Step 2A Prong 1. The claim recites the following abstract ideas:
perform regression of an objective variable at a prediction target time using one or more explanatory variables corresponding to a plurality of times before the prediction target time, based on time-series data of the explanatory variables and the objective variable; (This recites a mathematical concept and/or a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can perform time series regressions. See, for example, [specification, figure 8] for support that this recites a mathematical concept. See MPEP 2106.04(a)(2)(I, III).)
calculate coefficients corresponding to each time point of the explanatory variables; (This recites a mathematical concept and/or a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can calculate coefficients related to time-series regression models. See MPEP 2106.04(a)(2)(I, III).)
select, based on the calculated coefficients, a subset of the explanatory variables corresponding to the plurality of times; (This recites a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can select variables based on calculated coefficients. See MPEP 2106.04(a)(2)(III).)
create first data including the selected explanatory variables as a plurality of first variables and the objective variable at the prediction target time as a second variable; (This recites a mental process that can be performed in the human mind or by a human using pen and paper. See MPEP 2106.04(a)(2)(III).)
generate one or more grouping candidates by dividing the plurality of first variables in the first data into a plurality of groups using a predefined automatic generation method or a grouping method specified by a user; (This recites a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can generate grouping candidates. See MPEP 2106.04(a)(2)(III).)
generate, for each combination of the grouping candidates and one or more model architecture candidates, a prediction model configured to associate the first variables included in the respective groups with a predicted value of the second variable; (This recites a mathematical concept and a mental process that can be performed in the human mind or by a human using pen and paper. The examiner notes that the scope of the “prediction model” of the claim encompasses models such as linear regression [specification, 0034], which are mathematical concepts that are feasible to train/generate by a human mind. See MPEP 2106.04(a)(2)(I, III).)
calculate an evaluation value for each prediction model based on a difference between the predicted value of the second variable and a value of the second variable in the first data; (This recites a mathematical concept and a mental process that can be performed in the human mind or by a human using pen and paper. A human mind can calculate values based on differences between a prediction and an actual value. See MPEP 2106.04(a)(2)(I, III).)
and determine a grouping and a model architecture to be used, based on the evaluation value corresponding to each combination of the grouping candidates and the model architecture candidates. (This recites a mental process that can be performed