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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 07/20/2026 has been entered.
Status of the Claims
Claims 1, 5-6, and 18 have been amended. Claims 1, 3, 5-6, 10, 12-13, 15-16, and 18-21 are currently pending and 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 therefor, subject to the conditions and requirements of this title.
Claims 1, 3, 5-6, 10, 12-13, 15-16, and 18-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Claims 1, 3, 10, 12, and 19 each recites a non-transitory computer-readable recording medium (a product). Claims 5, 13, 15, and 20 each recites a method. Claims 6, 16, 18, and 21 each recites an apparatus comprising a processor. A product, a method, and an apparatus each falls within one of the four statutory categories of patent eligible subject matter.
Claim 1
Step 2A Prong 1: Generating a plurality of Betti series that is time series data based on Betti numbers obtained by applying persistent homology transform to a plurality of pseudo-attractors generated, respectively, from a plurality of pieces of time-series data is a mathematical calculation. In the instant specification, paragraphs [0041]-[0045] disclose Formulas (2) to (5) for generating a Betti series.
Generating a plurality of transformed Betti series in which a region with a larger radius when generating the Betti numbers is emphasized more than a region with a smaller radius, by thinning out the plurality of Betti series while decreasing a thinning interval is a mathematical calculation and a judgement and evaluation mental process which can reasonably be performed in the human mind with the aid of pencil and paper. In the instant specification, paragraph [0046] and Fig. 8 disclose an example of thinning out a Betti series. A person can reasonably perform this example by hand on a piece of paper. Paragraphs [0047]-[0049] disclose Formulas (6) to (7) for generating a transformed Betti series. The claim recites an abstract idea.
Step 2A Prong 2 and Step 2B: A non-transitory computer-readable recording medium having stored therein a machine learning program that causes a computer to execute a process amounts to generic computer components for applying the abstract ideas on a generic computer under MPEP 2106.05(f).
Training a neural network using the generated plurality of transformed Betti series as input features so as to update parameters of the neural network, the trained neural network being configured to output estimated labels for discrimination target data based on the updated parameters, the estimated labels indicating a change point in the discrimination target data amounts to mere instructions to apply the abstract ideas on a generic computer under MPEP 2106.05(f).
The additional elements as disclosed above, alone or in combination, do not integrate the abstract ideas into a practical application as they are generic computer functions as disclosed that are implemented to perform the abstract ideas disclosed above. The claim is directed to an abstract idea.
The additional elements as disclosed above, in combination with the abstract ideas, are not sufficient to amount to significantly more than the abstract ideas as they are generic computer functions as disclosed that are implemented to perform the abstract idea disclosed above. The claim is not patent eligible.
Claim 3 incorporates the rejections of claim 1.
Step 2A Prong 1: The abstract ideas of claim 1 are incorporated. The generating the plurality of transformed Betti series includes acquiring Betti numbers at intervals monotonically decreasing as a radius increases from Betti numbers of each radius included in the plurality of Betti series, and generating the plurality of transformed Betti series using the acquired Betti numbers of the respective radii are mathematical calculations. In the instant specification, paragraphs [0047]-[0049] disclose Formulas (6) to (7) for generating a transformed Betti series.
Step 2A Prong 2 and Step 2B: The claim does not recite any additional elements which, alone or in combination, would integrate the abstract ideas into a practical application. The claim does not recite any additional elements which, in combination with the abstract ideas, would be sufficient to amount to significantly more than the abstract ideas. The claim is not patent eligible.
Claim 5 recites a method that implements the same features as the non-transitory computer-readable recording medium of claim 1, and is therefore rejected for at least the same reasons.
In Step 2A Prong 2 and Step 2B, a processing circuit amounts to a generic computer component for applying the abstract ideas on a generic computer under MPEP 2106.05(f). The claim is not patent eligible.
Claim 6 recites an apparatus comprising a processor that implements the same features as the non-transitory computer-readable recording medium of claim 1, and is therefore rejected for at least the same reasons therein.
In Step 2A Prong 2 and Step 2B, at least one processor and at least one memory including computer program code, where the at least one memory and the computer program code are configured, with the at least one processor, to cause the apparatus to perform operations amounts to generic computer components for applying the abstract ideas on a generic computer under MPEP 2106.05(f). The claim is not patent eligible.
Claim 19 incorporates the rejection of claim 1.
Step 2A Prong 1: The abstract ideas of claim 1 are incorporated.
Step 2A Prong 2 and Step 2B: Inputting discrimination target data to the trained neural network and estimating labels for the discrimination target data to indicate a change point in the discrimination target data amounts to invoking computers merely as a tool to perform an existing process under MPEP 2106.05(f). The claim is not patent eligible.
Claim 10 incorporates the rejections of claim 19.
Step 2A Prong 1: The abstract ideas of claim 19 are incorporated.
Step 2A Prong 2: Outputting information relating to a graph of the estimated labels amounts to an insignificant extra-solution activity under MPEP 2106.05(g).
Step 2B: Outputting information relating to a graph of the estimated labels is analogous to presenting offers and gathering statistics, which is a well-understood, routine, conventional activity recognized by the courts under MPEP 2106.05(d)(II). The claim is not patent eligible.
Claim 12 incorporates the rejections of claim 19.
Step 2A Prong 1: The abstract ideas of claim 19 are incorporated.
Step 2A Prong 2: Displaying a graph of the estimated labels amounts to an insignificant extra-solution activity under MPEP 2106.05(g).
Step 2B: Displaying a graph of the estimated labels is analogous to presenting offers and gathering statistics, which is a well-understood, routine, conventional activity recognized by the courts under MPEP 2106.05(d)(II). The claim is not patent eligible.
Claim 20 recites a method that implements the same features as the non-transitory computer-readable recording medium of claim 19 and is therefore rejected for at least the same reasons.
Claims 13 and 15 each recites a method that implements the same features as the non-transitory computer-readable recording medium of claims 10 and 12, respectively, and are therefore rejected for at least the same reasons.
Claim 21 recites an apparatus comprising a processor that implements the same features as the non-transitory computer-readable recording medium of claim 19 and is therefore rejected for at least the same reasons.
Claims 16 and 18 each recites an apparatus comprising a processor that implements the same features as the non-transitory computer-readable recording medium of claims 10 and 12, respectively, and are therefore rejected for at least the same reasons.
Response to Arguments
The following are the Examiner’s responses to the Applicant’s arguments filed 07/20/2026.
Applicant’s First Argument Under 35 U.S.C. 101: On page 8, Applicant argues amended claim 1 does not amount to mere instructions to apply the abstract ideas on a generic computer, but indicates change point in the discrimination target data by using neural network trained by transformed Betti series.
Examiner’s Response: Applicant's arguments have been fully considered but they are not persuasive. In the 101 inquiry for claim 1, in Step 2A Prong 2, the entire limitation in lines 14-17 amounts to mere instructions to apply the abstract ideas on a generic computer under MPEP 2106.05(f).
The claim describes the types of training inputs and outputs of the neural network, and recites that the estimated labels, output by the neural network, indicate a change point in the discrimination target data. However, the claim recites only the idea of a solution or outcome and fails to recite details of how a solution to a problem is accomplished (see MPEP 2106.05(f), item 1). The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words “apply it.”
Specifically, the unsupervised learning as recited amounts to traditional unsupervised learning without any details that might provide a technological improvement. The limitation “the estimated labels indicating a change point in the discrimination target data” is merely a characteristic of the estimated labels. The claim does not explain the meaning of a “change point in the discrimination target data” such that it might provide a technological improvement. The claim does not explain how the neural network’s structure, operations, etc. use the transformed Betti series to output estimated labels that indicate a change point in the discrimination target data. Without these details, the limitation does not integrate a judicial exception into a practical application.
Applicant’s Second Argument Under 35 U.S.C. 101: On pages 8-9, Applicant cites PTAB decision in Ex Parte Desjardins, and further argues that amended claim 1 relates input feature of transformed Betti series to training of neural network and updated parameters for outputting estimated labels of change point by trained neural network. Therefore, amended claim 1 is not only a simple instruction to apply an abstract idea on a standard computer, but can be integrated into the practical application. Thus, amended claim 1 is patent eligible.
Examiner’s Response: Applicant's arguments have been fully considered but they are not persuasive. Examiner respectfully disagrees that pending claim 1 is similar to Ex Parte Desjardins. The claims in Desjardins solve a technical problem of catastrophic forgetting in machine learning. The limitations in pending claim 1 as a whole are NOT an analogous factual setting to the claims at issue in Desjardins. Pending claim 1 does not integrate the abstract ideas into a practical application for the reasons provided in the Examiner’s response to the Applicant’s first arguments.
Conclusion
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/A.H.J./Examiner, Art Unit 2127
/JEREMY L STANLEY/Examiner, Art Unit 2127
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