DETAILED ACTION
Claims 1, 3-5, and 7-20 are presented for examination.
Claims 1, 3, 7, 8 and 15 have been amended.
Claims 2 and 6 have been cancelled.
This office action is in response to the amendment submitted on 28-Apr-2026.
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 .
Response to Arguments – 35 USC 101
On pgs. 9-14 of the Applicant/Arguments Remarks (hereinafter ‘Remarks’), Applicant argues the amended claims have overcome the rejection under 35 USC 101. Examiner respectfully disagrees and finds Claim 2 of Example 47 from the July 2024 Subject Matter Eligibility Examples relevant.
The applicant argues on pg. 9 the invention fills in missing gaps in training NN with graph representations instead of original data for security considerations. However, as shown in the 103 rejection the technology of representing data as graphs and using it for training purposes does exist in the field and the current general linkage as indicated in the amendment made to the claims do not amount to a practical application of the abstract idea as there is no logic or claimed steps that detail the process taken by the trained NN in filling in the gaps based on the combined simulated data.
Applicant's arguments fail to comply with 37 CFR 1.111(b) because they amount to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims patentably distinguishes them from the references.
Additionally, the applicant argues the claimed steps require an objective function calculated at every step and hence can’t be done in the abstract.
The applicant is reminded that objective functions are evaluations. The courts do not distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer. As the Federal Circuit has explained, "[c]ourts have examined claims that required the use of a computer and still found that the underlying, patent-ineligible invention could be performed via pen and paper or in a person’s mind." Versata Dev. Group v. SAP Am., Inc., 793 F.3d 1306, 1335, 115 USPQ2d 1681, 1702 (Fed. Cir. 2015). See also Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1318, 120 USPQ2d 1353, 1360 (Fed. Cir. 2016) (‘‘[W]ith the exception of generic computer-implemented steps, there is nothing in the claims themselves that foreclose them from being performed by a human, mentally or with pen and paper.’’); Mortgage Grader, Inc. v. First Choice Loan Servs. Inc., 811 F.3d 1314, 1324, 117 USPQ2d 1693, 1699 (Fed. Cir. 2016) (holding that computer-implemented method for "anonymous loan shopping" was an abstract idea because it could be "performed by humans without a computer").
The applicant on pg. 11 argues there are practical applications to the exception in the field of medical coding. However, the claim language is written at a high level of generality and does not reflect any medical application, let alone solving a problem, or ‘automating’ a process in the field of medical record processing.
Again these arguments fail to comply with 37 CFR 1.111(b) because they amount to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims patentably distinguishes them from the references.
Applicant's arguments have been fully considered but they are not persuasive. Rejection under 35 USC 101 is maintained.
Claim Objections
Claims 1, 8 and 15 are objected to because of the following informalities: the word ‘date’ is a misspelling of ‘data’. Appropriate correction is required.
Claim Rejections - 35 USC § 112
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.
The following is a quotation of 35 U.S.C. 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.
Claims 1, 3-5, and 7-20 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.
Claims 1, 8, and 15 teach a large amount of data. The specification additionally does not define ‘large volume’ (Specification [0014] “Data management systems, such as Master Data Management (MDM) systems, that organize large amounts of data for organizations often rely on data models that provide underlying definitions and relationships between types of data”). Large is a relative term and is rejected for its lack of clarity.
Claims 3-5 and 7, 9-14, and 16-20 are dependents on 1, 8, and 15 respectively and are rejected for the same reason.
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, and 7-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1
Step 1: Statutory class – process.
Step 2A Prong One: Does the claim recite an abstract idea, law of nature or natural phenomenon?
Yes
“3) Mental processes – concepts performed in the human mind (including an observation, evaluation, judgment, opinion) (see MPEP § 2106.04(a)(2), subsection III).” MPEP § 2106.04(a).
The claims are directed to an abstract idea of data processing and analysis. The claim recites:
Determining information gaps to establish relationships between data received; a data model to fill information gaps wherein the data model includes nodes representing types of information and edges representing relationships between the types of information
generating a set of digital twin replicas, each corresponding to a respective node of the data model;
generating output from said set of digital twin replicas, wherein each digital twin node is directed as an incoming edge input and directed to generate a corresponding output, wherein the output has a singular value or vector denoting a task
utilizing the set of digital twin replicas to generate simulated data corresponding to the types of information represented by the nodes of the data model; wherein said simulated data are alternative of establishing data relationships
combining the simulated data generated by the set of digital twin replicas into a combined set of simulated data to provide a prediction of missing information gaps based, at least in part, on the edges of the data model.
training a neural network using the simulated data combined to predict future values of information represented by the nodes according to relationship between types of information.
Determining, Generating, combining, and training are mental processes and mathematical manipulations.
By way of example, one can mentally determine information gaps in the provided data, create a data driven model representing the digital twin from a set of data, mentally manipulate the data, simulate certain actions and predictions, combine it as necessary, update it with production data and train a machine learning model to predict future values.
Step 2A Prong Two: Does the claim recite additional elements that integrate the judicial exception into a practical application?
No.
The additional elements are:
a computer implemented method
extracting information from a large amount of data received
Using said simulated data and said neural network that is trained to provide future information gaps and establish data relationships
computer implemented method is mere instructions to apply an exception on a generic computer. MPEP § 2106.05(f).
extracting is an insignificant extra solution activity – mere data collection. MPEP § 2106.05(g).
using the simulated data is mere instructions to apply an exception on a generic computer. MPEP § 2106.05(f).
Step 2B: Does the claim recite additional elements that amount to significantly more than judicial exception?
No. The additional elements are a generic computer performing conventional functions and mere data gathering.
Claim 3 recites the digital twin replica of the set of digital twin replicas generates, as output, a row of simulated data, which is a mathematical process under Step 2A Prong One.
a neuron of the plurality of neurons generates simulated data corresponding to a respective column of the row of simulated data, which is a mathematical process under Step 2A Prong One.
Claim 4 recites the digital twin replica of the set of digital twin replicas corresponds to a respective table in a master data management (MDM) system, which is a mental process under Step 2A Prong One.
the row of simulated data corresponds to a row of the table, which is a mental process under Step 2A Prong One.
Claim 5 recites evaluating the row of simulated data utilizing a loss minimization based objective function, which is a mathematical process under Step 2A Prong One.
Claim 7 recites receiving a graph corresponding to the data model, the graph including at least one incomplete type of information, which is mere data gathering under Step 2A Prong Two and Step 2B.
utilizing the trained graph neural network to complete the at least one incomplete type of information, which is a mental/mathematical process under Step 2A Prong One.
Claim 8 recites a computer program product comprising: (statutory category – machine)
one or more computer readable storage media and program instructions collectively stored on the one or more computer readable storage media, the program instructions executable by one or more computer processors to cause the one or more computer processors to perform a method comprising, which is mere instructions to apply an exception on a generic computer under Step 2A Prong Two and 2B. MPEP § 2106.05(f).
The remaining limitations are similar to claim 1 and are rejected under the same rationale.
Claim 9 recites the digital twin replica of the set of digital twin replicas includes a neural architecture comprising a plurality of neurons, which is a mathematical process under Step 2A Prong One.
Claims 10-12 recite limitations similar to claims 3-5 respectively, and are rejected under the same rationale.
Claim 13 recites training a graph neural network utilizing the combined set of simulated data as training data, which is a mathematical process under Step 2A Prong One.
Claim 14 recite limitations similar to claims 7, and is rejected under the same rationale.
Claim 15 recites a computer system comprising: (statutory category – machine)
one or more computer processors; and
one or more computer readable storage media; wherein:
the one or more computer processors are structured, located, connected and/or programmed to execute program instructions collectively stored on the one or more computer readable storage media; and the program instructions, when executed by the one or more computer processors, cause the one or more computer processors to perform a method comprising, which is mere instructions to apply an exception on a generic computer under Step 2A Prong Two and 2B. MPEP § 2106.05(f).
The remaining limitations are similar to claim 1 and are rejected under the same rationale.
Claims 16-20 recite limitations similar to claims 9, 3-5 and 7 respectively, and are rejected under the same rationale.
Allowable Subject Matter
Claims 1, 3-5, and 7-20 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 101, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
The following is an examiner’s statement of reasons for allowance:
The cited references are deemed the closest prior art made of record to the claimed invention:
Cella et al. (US20220108262A1) in view of Iida et al. (US20220253321A1) and further in view of Ayush et al. (US-20210342701-A1).
However, the reference(s) or any reference of record or combination of references, do not disclose or suggest:
combining the simulated data generated by the set of digital twin replicas into a combined set of simulated data to provide a prediction of missing information gaps, based at least in part, on the edges of the data model
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Zhang et al (Relation Prediction via Graph Neural Network in Heterogeneous Information Networks with Missing Type Information): discloses predicting missing information in GNN. Please see Fig. 1.
US20230098596A1: Discloses digital twins, data models and machine learning in a VR context.
US20220083707A1: Discloses digital twins and data models.
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.
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/A.E.D./Examiner, Art Unit 2199 /LEWIS A BULLOCK JR/Supervisory Patent Examiner, Art Unit 2199
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