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 .
DETAILED ACTION
Status of the Application
Claims 1-26 are currently pending in this case and have been examined and addressed below. This communication is a Final Rejection in response to the Amendments to the Claims and Remarks filed on 08/11/2026.
Claims 1, 4, 19-21, and 25-26 are currently amended.
Claim 27 is canceled and not considered at this time.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 08/25/2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being 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 therefor, subject to the conditions and requirements of this title.
Claims 1-26 are rejected because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Claims 1-18 and 19-24 fall within the statutory category of an apparatus or system. Claim 25 falls within the statutory category of a process. Claim 26 falls within the statutory category of an article of manufacture as a computer-readable medium.
Step 2A, Prong One
As per Claims 1, 25 and 26, the limitations of suggest any one or more candidates of a plurality of candidates each representing a combination of factor parameters contributing to a decision of a label provided to the target and a label provided to the associated target; learning, by referring to the plurality of records, an estimation model for each calculation candidate of a calculation candidate being a part of the plurality of candidates; calculating performance that estimates a label provided to a target from a parameter value in which a parameter related to a combination represented by the each calculation candidate is acquired for the target; calculating a rating value associated with the each calculation candidate, based on the calculated performance; learning a rating model by referring to a rating value calculated for the calculation candidate having a small number of times of learning; and estimating a rating value associated with each estimation candidate of an estimation candidate other than the calculation candidate among the plurality of candidates prior to learning an estimation model for the estimation candidate, wherein the rating value associated with the estimation candidate is estimated without calculating performance of the estimation candidate, and wherein the rating value associated with the estimation candidate is estimated without first learning an estimation model for the estimation candidate, under its broadest reasonable interpretation, covers performance of the limitation in the mind. The steps of learning an estimation model for each calculation candidate, calculating performance that estimates a label provided to a target from a parameter value, calculating a rating value associated with each calculation candidate, learning a rating model, and estimating a rating value associated with each estimation candidate are concepts performed including observation, evaluation, judgement and opinion in the human mind. If a claim limitation, under its broadest reasonable interpretation, covers the performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. The steps of calculating performance, calculating a rating value, and estimating a rating value can also fall into the grouping of mathematical concepts as mathematical relationships and calculations can be used to carry out the calculating step. As per MPEP 2106.04(a), a claim can recite more than one judicial exception and claims which recite a series of steps that recite mental steps which are also mathematical calculations are identified as both. Accordingly, the claims recite an abstract idea.
As per Claim 19, the limitations of select, as a prediction candidate, a useful candidate in which the already acquired examination value fulfills a combination of examination items related to a useful candidate, from a plurality of useful candidates being a plurality of useful candidates and each representing a combination of examination items; and estimate a prognosis of the patient, under its broadest reasonable interpretation, covers performance of the limitation in the mind. The steps of selecting a useful candidate and estimate a prognosis of the patient are concepts performed including observation, evaluation, judgement and opinion in the human mind. If a claim limitation, under its broadest reasonable interpretation, covers the performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
Step 2A, Prong Two
The judicial exception is not integrated into a practical application because the additional elements and combination of additional elements do not impose meaningful limits on the judicial exception. In particular, the claims recite the additional elements – a suggestion device comprising a memory storing instructions and one or more processors configured to execute the instructions, and a processor-implemented calculator, estimator, and outputter in Claim 1. Claim 19 includes a suggestion system comprising the suggestion device described above, a terminal device communicatively coupled to the suggestion device, comprising a memory and one or more processors, and a processor-implemented examination value presenter, prediction candidate selector, prognosis estimator, and a prognosis presenter. Claim 26 includes a calculator, an estimator, and an outputter. The suggestion device and terminal device comprising memory storing instructions and processors; processor-implemented calculator, estimator, outputter, presenter, and selector; and a processor-implemented examination value presenter, prediction candidate selector, prognosis estimator, and a prognosis presenter in these steps are recited at a high-level of generality, such that it amounts to no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims also recite the additional elements of using the learned estimation model to calculate performance, using an estimation model learned from the estimation candidate, and using the learned rating model, which amounts to mere instructions to apply the exception. As per MPEP 2106.05(f)(2), the use of a mathematical algorithm to apply the abstract idea has been found to be mere instructions to apply the exception. The claims also recite outputting, as the useful candidate, a calculation candidate associated with a rating value being high-ranking among the calculated or estimated rating values (Claims 1, 25 and 26) and presenting an already-acquired examination value on a screen and presenting the estimated prognosis on the screen (Claim 19), which amounts to insignificant extra-solution activity, as in MPEP 2106.05(g), because the steps of outputting a calculation candidate and presenting the examination value and prognosis are mere data outputting in conjunction with the abstract idea where the limitation amounts to necessary data gathering and outputting, (i.e., all uses of the recited judicial exception require such data gathering or data output). See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering). Because the additional elements do not impose meaningful limitations on the judicial exception, the claim is directed to an abstract idea.
Step 2B
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea. As discussed above with the respect to integration of the abstract idea into a practical application, the additional element of a suggestion device comprising a memory storing instructions and one or more processors configured to execute the instructions, and a processor-implemented calculator, an estimator, and an outputter in Claims 1 and 26 and a suggestion system comprising the suggestion device described above, a terminal device communicatively coupled to the suggestion device, comprising a memory and one or more processors, and a processor-implemented examination value presenter, prediction candidate selector, prognosis estimator, and prognosis presenter in Claim 19 to perform the method of the invention amounts to no more than mere instructions to apply the exception using a generic computing component. The system including the "suggestion device” are recited at a high level of generality and are recited as generic computer components by reciting a computer executing a program (Specification, [0018]), and a terminal such as a personal computer ([0229]), which do not add meaningful limitations to the abstract idea beyond mere instructions to apply an exception. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claims also recite using the learned estimation model to calculate performance, using an estimation model learned from the estimation candidate, and using the learned rating model which amounts to mere instructions to apply the exception. The specification describes the estimation model as various machine learning models and classification models such as decision tree, random forest, etc. (Specification [0029]), which are known mathematical algorithms. The learned rating model is not explicitly defined but is described as using deep learning ([0082]), which is a known algorithm. The claims also include the additional elements of outputting, as the useful candidate, a calculation candidate associated with a rating value being high-ranking among the calculated or estimated rating values (Claims 1, 25 and 26) and presenting an already-acquired examination value on a screen and presenting the estimated prognosis on the screen which are elements that are well-understood, routine and conventional computer functions in the field of data management because they are claimed at a high level of generality and include receiving or transmitting data as well as presenting offers, which have been found to be well-understood, routine and conventional computer functions by the Court (MPEP 2106.05(d)(II)(i) Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) ("Unlike the claims in Ultramercial, the claims at issue here specify how interactions with the Internet are manipulated to yield a desired result‐‐a result that overrides the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink." (emphasis added) and (iv) Presenting offers and gathering statistics, OIP Techs., 788 F.3d at 1362-63, 115 USPQ2d at 1092-93). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of the computer or improves another technology. The claims do not amount to significantly more than the underlying abstract idea.
Dependent Claims
Dependent Claims 2-18 and 20-24 add further limitations which are also directed to an abstract idea. Claims 2-3, 6, 11-13 include limitations which further specify or limit the concepts of the independent claims and are therefore directed to the same abstract idea. Claim 4 includes removing an estimation candidate having the associated rating value being low-ranking from the plurality of candidates which is a mental process. Claim 5 includes generating training data from a training record, generating test data from a test record being acquired by removing the training record from the plurality of records which fall into the abstract grouping of a mental process. Claim 7 includes obtaining performance from candidates by setting the training record and test record to be common, determining a competition result, and updating each rating values of the plurality of candidates based on the determined competition result which fall into the abstract grouping of a mental process. Claim 8 includes extracting a candidate that has not learned an estimation model for the candidate which fall into the abstract grouping of a mental process. Claim 9 describes narrowing down the plurality of candidates by a set of mathematical concepts. Claim 10 describes a particular display of outputting data which further specifies the output of data which amounts to insignificant extra-solution similar to the independent claims. Claim 14 adds an external device which is a general purpose computing device, as described in the specification [0173] as achieved by a computer. The external device accepts data and presents data which amount to mere data gathering and outputting, which is insignificant extra-solution activity that is well-understood, routine, and conventional receiving and transmitting data. Claims 15-16 further limits or specifies Claim 14. Claim 17 includes estimating a plurality of labels which is a mental process and also includes outputting data and transmitting data which amount to mere data outputting that is insignificant extra-solution activity that is well-understood, routine, and conventional receiving and transmitting data. Claim 18 includes the same limitations as Claim 19 and is directed to the same abstract idea for the same reasons. Claim 20 includes selecting a useful candidate which amounts to a mental process. The claim also includes presenting data which amounts to mere data outputting that is insignificant extra-solution activity that is well-understood, routine, and conventional similar to presenting offers. Claims 21-24 further specifies and limits the presenting of data of Claim 20 and is therefore directed to the same abstract idea. Because the additional elements do not impose meaningful limitations on the judicial exception and the additional elements are well-understood, routine and conventional functionalities in the art, the claims are directed to an abstract idea and are not patent eligible.
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 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.
Claims 1- 26 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 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 U.S.C. 112, the applicant), regards as the invention.
The term “small number of times of learning” in claims 1, 25 and 26 is a relative term which renders the claim indefinite. The term “small” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. A small number of time of learning is not defined and therefore it is not clear how many number of times of learning would be required by the claim to be small.
As per Claims 2-24, the claims depend on Claims 1, 19, and 26 and do not remedy the indefiniteness issues of Claims 1, 19, and 26. As dependent claims inherit the deficiencies of the claims they depend on, they are also rejected.
Response to Arguments
Applicant’s arguments, see Pages 18-24, “Rejections under 35 U.S.C. §101”, filed 08/11/2026 with respect to claims 1-26 have been fully considered but they are not persuasive.
Applicant argues that the present claims are not directed to a mental process because the claims recite a specific processing architecture that is a specific technological technique for reducing the amount of processing associated with estimation-model learning and candidate competition. Examiner respectfully disagrees. The reduction in the amount of processing is not due to a technical solution to a technical problem. Any reduction in processing is a result of the estimation model learning and candidate competition which is part of the abstract idea itself. Therefore any improvement is an improvement to the abstract idea itself and not an improvement to the computer or a technological improvement. Additionally, Applicant argues that the claims improve the efficiency of candidate evaluation by reducing estimation-model learning operations and candidate competitions through rating-model-based evaluation of estimation candidates. Examiner respectfully disagrees. The efficiency of the candidate evaluation is not due to a technological improvement to a technical problem, but rather is a result of the chosen order of steps of the abstract idea itself. Therefore, any improvement which results is an improvement to the abstract idea itself.
Applicant argues that claim 1 is directed to a unique ordered combination of technical elements that provides a neural networked, superior computer-based tool that employs techniques utilizing hardware for computing a specific technological technique for reducing the amount of processing in a manner that is more effective and more efficient than any generic computer could accomplish. Examiner respectfully disagrees. Claim 1 recites hardware including a memory storing instructions and one or more processors to execute the steps of the invention. These computer components are recited at a high-level of generality and are no more than general purpose computers. The specification discloses that the device of the claims is embodied as a computer executing a program ([0018]). Therefore, the steps of the claims are applied by a generic computer, which amounts to mere instructions to apply the exception and not a technical improvement. The ordered combination of elements of the claims are directed to the abstract idea itself and therefore any improvement in efficiency or effectiveness resulting from the steps of the claims is an improvement to the abstract idea itself.
Applicant argues that the processing architecture of rating values for estimation candidate being generated before learning estimation models is a novel and unconventional approach and therefore not abstract. Examiner notes that novelty and eligibility are two separate and distinct considerations. Whether or not a claim is novel has no impact on the determination of subject matter eligibility.
Applicant argues that the unique ordered combination of technical elements recited in claim 1 integrates the abstract idea into a practical application. Applicant further argues that the process steps cannot be accomplished with just any computer. Examiner respectfully disagrees. Claim 1 recites a suggestion device to execute the steps of the claim. The specification teaches that the suggestion device is achieved by a computer executing a program ([0018]). This clearly teaches that the technical elements of the claims, the memory storing instructions and processor to execute the instructions which make up the suggestion device are merely a known computer. Use of a general purpose computer to carry out the steps of the abstract idea amounts to mere instructions to apply the exception, as per MPEP 2106.05(f)(2). Applicant also argues the claims solve a technical problem in the field of data science. Examiner respectfully disagrees. Narrowing candidates down to a useful candidate while suppressing learning of the estimation model and the number of competitions is not a technical problem. Improving the time to perform a calculation and decision of what data to include in the calculation is an improvement to the abstract idea itself and not an improvement to technology.
Applicant argues that the claims recite significantly more than the abstract idea because the claim recites additional elements which are not well-understood, routine, and conventional. Specifically, Applicant argues that the claims provide a specific ordered combination of elements that are not well-understood, routine, and conventional. However, Applicant does not provide what combination of elements are now well-understood, routine, and conventional and therefore, the argument is moot. Examiner is not persuaded that the claims provide any additional elements or combination of elements which are not well-understood, routine, and conventional.
Applicant argues that the claims provide a specific ordered combination of elements that amount to meaningful limitations. However, as discussed above, Applicant does not specify what limitations amount to meaningful limitations. Applicant further argues that the present invention solves the technical problem of a calculation amount and calculation time which are large and an explosion in a competition number occurs. Examiner respectfully disagrees because the extent and time of a calculation is not a technical problem. Applying the calculation to a general purpose computer results in the improvement, and therefore this is not a technical improvement to a technical problem.
Applicant’s arguments, see Pages 24-30, “Rejections under 35 U.S.C. §112”, filed 08/11/2026 have been fully considered.
With regard to the 112f Interpretation of Claims 1-26, the arguments are persuasive due to the amendments to the claims and therefore the interpretation of 05/15/2026 has been withdrawn.
With regard to the 112b rejections of claims 1-24 and 26-27, the arguments are persuasive due to the amendments to the claims and therefore the rejection of 05/15/2026 has been withdrawn.
With regard to the 112a rejections of claims 1-24 and 26-27, the arguments are persuasive due to the amendments to the claims and therefore the rejection of 05/15/2026 has been withdrawn.
Applicant’s arguments, see Pages 30-38, “Rejections under 35 U.S.C. §§102 and 103”, filed 08/11/2026 with respect to claims 1-26 have been fully considered and they are persuasive. Therefore, the rejection of 05/15/2026 has been withdrawn.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Evangeline Barr whose telephone number is (571)272-0369. The examiner can normally be reached Monday to Friday 8:00 am to 4:00 pm.
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/EVANGELINE BARR/Primary Examiner, Art Unit 3682
