DETAILED ACTION
This Action is responsive to Claims filed 07/14/2025.
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 .
Status of the Claims
Claims 1, 8, 15, 22, 25, 27, 30, 32, and 34-35 have been amended. Claims 1-2, 8, 15-16, 22, 24-25, 27, 29-30, 32, and 34- 35 are pending.
Response to Arguments
Applicant's arguments filed 07/14/2025 regarding the 35 U.S.C. 101 Rejection of Claims 1-2, 8, 15-16, 22, 24-25, 27, 29-30, 32, and 34- 35 have been fully considered but they are not persuasive.
The Applicant argues, without supporting claim language or explanation, that the alleged abstract idea mental process steps of the independent claims are not practically performed within the human mind. There is currently no claim language precluding the “selecting…”, “setting…”, “calculating…”, “calculating…”, “setting…”, and “setting…”, steps from being practically performed within the human mind or with the aid of pen and paper. The claim limitations are recited highly generally, only tied to a generic computer performed generic computer functions or highly generally to a neural network. Based on the Applicant’s Specification (see the 35 U.S.C. 112(a) Rejection below), the alleged abstract idea mental process steps are performed by a generic computing device without further detail as to a specific structure or implementation. These steps appear to be performed as data-preprocessing before using the expanded anchor window in the training of the neural network (See newly amended limitations “the training comprises: using the expanded first anchor window…”). The Examiner contends the BRI of the amended claims continues to reflect a series of interpretable abstract idea mental process steps, then applied in the training of a neural network, in order to realize the alleged improvements to the functioning of a computer or other technological field. The Applicant is reminded that the improvement cannot come from the abstract idea mental process steps (See MPEP 2106.05(a)). See the updated 35 U.S.C. 101 Rejection below.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 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 U.S.C. 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 1-2, 22, and 24-25 rejected under 35 U.S.C. 112(a) or 35 U.S.C. 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 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claims 1-2, 22, and 24-25 recite (either directly, or by way of dependency) the “setting…”, “calculating…”, “calculating…”, “setting…”, “setting…”, and “iteratively expanding…” steps are performed “by the neural network of the computing device…” (or similar, emphasis added). There is no written description supporting that the neural network performs these actions, versus the computing device, which is described in the Specification.
Claim Rejections - 35 USC § 101
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1-2, 8, 15-16, 22, 24-25, 27, 29-30, 32, and 34-35 rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more; and because the claims as a whole, considering all claim elements both individually and in combination, do not amount to significantly more than the abstract idea, see Alice Corporation Pty. Ltd. v. CLS Bank International, et al, 573 U.S. (2014). In determining whether the claims are subject matter eligible, the Examiner applies the 2019 USPTO Patent Eligibility Guidelines. (2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, Jan. 7, 2019.)
Step 1:
Claims 1, 2, 22, and 24-25 recite a method of using a computing device to determine a window size in variate time series data, which falls under the statutory category of a process. Claims 8, 27 and 29-30 recite a computer program product for determining a window size in variate time series data, which falls under the statutory category of a manufacture. Claims 15, 16, 32 and 34-35 recite an apparatus comprising: a memory configured to store instructions; and a processor configured to execute the instructions, which falls under the statutory category of a machine.
Step 2A – Prong 1:
Claim 1 recites an abstract idea, law of nature, or natural phenomenon. The limitations of “selecting anchor windows to narrow representation machine learning variations during iterative training of a neural network of a computing device”, “setting, by the neural network of the computing device, a moving window size for the variate time series data;”, “calculating, by the neural network of the computing device, moving window averages based on the moving window size, wherein each moving window average of the moving window averages corresponds to a respective time series instance of the plurality of time series instances;”, “calculating, by the neural network of the computing device, an aggregated standard deviation vector comprising a plurality of standard deviations, wherein each standard deviation of the plurality of standard deviations correspondscomputing device, a first anchor window, of the anchor windows, with a length corresponding to the moving window size to encompass a first position of a first largest standard deviation of the plurality of standard deviations, wherein the first largest standard deviation corresponds to a first time series instance that has largest contrast among within the plurality of variate time series instances data;”, and “setting, by the neural network of the computing device, a second anchor window, of the anchor windows, with the length corresponding to the moving window size to encompass a second position of a second largest standard deviation of the plurality of standard deviations in the variate time series data;” Under the broadest reasonable interpretation, cover a mental process including an observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper. Setting a window size, calculating an average, calculating standard deviation(s), setting an anchor window, and setting a second anchor window are steps practically performed within the human mind or with the aid of pen and paper. These limitations therefore fall within the mental process group.
Step 2A – Prong 2:
The additional elements of claim 1 do not integrate the abstract idea into a judicial exception. The claim recites the additional elements “a computing device” which is recognized as generic computer components recited at a high level of generality. Although they have and execute instructions to perform the abstract idea itself, this also does not serve to integrate the abstract idea into a practical application as it merely amounts to instructions to "apply it." (See MPEP 2106.04(d)(2) indicating mere instructions to apply an abstract idea does not amount to integrating the abstract idea into a practical application).
The additional elements of “a neural network”, “anchor windows”, “variate time series data”, “time series instances”, “a moving window size”, “moving window averages”, “an aggregated standard deviation vector”, “a neural network”, “positive samples”, and “negative samples” are recognized as non-generic computer components, but are recited at a high level of generality and are found to generally link the abstract idea to a particular technological environment or field of use (See MPEP 2106.05(h)).
The additional elements recited in the limitations “receiving, by the neural network of the computing device, the variate time series data including a plurality of time series instances;” and “iteratively expanding, by the neural network of the computing device, the first anchor window to include a second time series instance, of the plurality of time series instances, encompassed by the second anchor window;” are found to be insignificant extra solution data retrieval or transmittal steps (See MPEP 2106.05(g)).
The additional elements recited in the limitations “training, by the computing device, the neural network based on the expansion of the first anchor window, one or more positive samples, and one or more negative samples, wherein the training comprises:”, “using the expanded first anchor window as an input to the neural network to decrease a number of training iterations required by the neural network to reach a specific accuracy threshold,” and “and wherein the training of the neural network is to distinguish between similar and dissimilar time series instances with reduced classification variance across a plurality of training runs of the neural network.” are found to be mere instructions to apply the abstract idea of propagating a vector into functions and learning model parameters (See MPEP 2106.04(d)(2) indicating mere instructions to apply an abstract idea does not amount to integrating the abstract idea into a practical application).
Step 2B:
The only limitation on the performance of the described method is a limitation reciting “a computing device” These elements are insufficient to transform a judicial exception to a patentable invention because the recited elements are considered insignificant extra-solution activity (generic computer system, processing resources, links the judicial exception to a particular, respective, technological environment). The claim thus recites computing components only at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using generic computer components; mere instructions to apply an exception using a generic computer component cannot provide an inventive concept (see MPEP 2106.05(f)).
The additional elements of “a neural network”, “anchor windows”, “variate time series data”, “time series instances”, “a moving window size”, “moving window averages”, “an aggregated standard deviation vector”, “a neural network”, “positive samples”, and “negative samples” are recognized as non-generic computer components, but are recited at a high level of generality and are found to generally link the abstract idea to a particular technological environment or field of use (See MPEP 2106.05(h)).
The additional elements recited in the limitations “receiving, by the neural network of the computing device, the variate time series data including a plurality of time series instances;” and “iteratively expanding, by the neural network of the computing device, the first anchor window to include a second time series instance, of the plurality of time series instances, encompassed by the second anchor window;” are acknowledged to be well-understood, routine, conventional activity (see, e.g., court recognized WURC examples in MPEP 2106.05(d)(II)).
The additional elements recited in the limitations “training, by the computing device, the neural network based on the expansion of the first anchor window, one or more positive samples, and one or more negative samples, wherein the training comprises:”, “using the expanded first anchor window as an input to the neural network to decrease a number of training iterations required by the neural network to reach a specific accuracy threshold,” and “and wherein the training of the neural network is to distinguish between similar and dissimilar time series instances with reduced classification variance across a plurality of training runs of the neural network.” are found to be mere instructions to apply the abstract idea (See MPEP 2106.05(f) indicating mere instructions to apply an abstract idea does not recite significantly more).
Taken alone or in ordered combination, these additional elements do not amount to significantly more than the above-identified abstract idea. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation.
For the reasons above, claim 1 is rejected as being directed to non-patentable subject matter under §101. This rejection applies equally to independent claims 8 and 15.
Claim 8 recites similar limitations to claim 1, with the inclusion of generic computer component additional elements “A computer program product”, “computer readable storage medium”, and “a processor” These additional elements have been evaluated under step 2A Prong 2 and reevaluated under step 2B and found to be recited at high levels of generality.
Claim 15 recites similar limitations to claim 1, with the inclusion of generic computer component additional elements “a memory” and “a processor” These additional elements have been evaluated under step 2A Prong 2 and reevaluated under step 2B and found to be recited at high levels of generality.
Dependent Claims:
Claim 2 (16) merely details refinements to the data gathered or manipulated. The
additional element “multivariate time series data” which, while recognized as not being a generic computer component, serves to generally link the abstract idea to a specific field of use or technological environment (See MPEP 2106.05(h)).
Claim 22 (Claims 27 and 32) recites an abstract idea mental process “determining that the first anchor window and the second anchor window are neighboring within the variate time series data;”
The additional elements recited have been evaluated under Steps 2A and 2B and found to be data gathering or data manipulation (“iteratively expanding, based on the determining that the first anchor window and the second anchor window are neighboring within the variate time series data, the first anchor window to include the second time series instance encompassed by the second anchor window, wherein the first anchor window and the second anchor window are combined to form an expanded anchor window;”) (See MPEP 2106.05(g)) and MPEP 2106.05(d)(II)) and mere instructions to apply the abstract idea (“training, by the computing device, the neural network iteratively based on the expanded anchor window.”) (See MPEP 2106.05(f)).
The additional element “an expanded anchor window” which, while recognized as not being a generic computer component, serves to generally link the abstract idea to a specific field of use or technological environment (See MPEP 2106.05(h)).
Claim 24 (Claims 29 and 34) recites and abstract idea mental process step (“sorting the plurality of standard deviations of the aggregated standard deviation vector in descending order;”) and further refinements to the “sorting…” abstract idea.
Claim 25 (Claims 30 and 35) recites an abstract idea mental process step “combining any anchor windows within the anchor windows that are neighboring within the variate time series data, wherein at least one anchor window of the anchor windows is combined with second anchor window to generate an expanded anchor window, wherein performing triplet loss representation learning is based on the set of anchor windows including the expanded anchor window.”
The additional elements recited have been evaluated under Steps 2A and 2B and found to be mere instructions to apply the abstract idea (“training the neural network iteratively based on the expanded anchor window.”) (See MPEP 2106.05(f)).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GRIFFIN T BEAN whose telephone number is (703)756-1473. The examiner can normally be reached M - F 7:30 - 4:30.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Li Zhen can be reached at (571) 272-3768. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/GRIFFIN TANNER BEAN/Examiner, Art Unit 2121
/Li B. Zhen/Supervisory Patent Examiner, Art Unit 2121