DETAILED ACTION
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 Claims
This action is responsive to Applicant’s claims filed 07/29/2026.
Claims 1-15 are currently pending and have been examined here.
Response to Arguments
Applicant’s arguments, see pages 8-15 of Applicant’s response filed 07/29/2026, with respect to the 35 U.S.C. 101 rejections have been fully considered, but they are not persuasive.
Applicant argues, on pages 8-9, and 12-15, that the combining of positive samples, hard negative samples, soft negative samples and mixed samples allows for training of a machine learning model with much greater accuracy and thereby improves the performance of a machine learning, therefore, the claims are directed to patent eligible subject matter. Examiner respectfully disagrees. Examiner respectfully notes that the alleged improvement is not to the machine learning model itself, but rather to the abstract idea. Using such types of data would bring forth a more accurate risk/value if a prediction were made outside the realm of the machine learning model recited, using non-machine learning based prediction models. Therefore, the improvement is not to the machine learning model itself, but to the abstract idea which is merely required to be “applied” using a machine learning model. It is important to keep in mind that an improvement in the abstract idea itself (e.g. a recited fundamental economic concept) is not an improvement in technology. MPEP 2106.06(a)(II) Furthermore, the claims do no more than “apply” the use of such data using a machine learning model to make three predictions. “Patents that do no more than claim the application of generic machine learning to new data environments, without disclosing improvements to the machine learning models to be applied, are patent ineligible under § 101." Recentive Analytics, Inc. v. Fox. Corp., Fed Cir. No. 2023-2437 (Apr. 18, 2025) (slip op. at 18). Since the claims, at most, represent an improvement to the abstract idea itself, and since the claims do no more than “apply” the abstract idea of generating such data sets and using them to make predictions using a machine learning model, Applicant’s arguments are unpersuasive.
Applicant argues, on pages 10-11, that the claimed limitations cannot be performed by a human using their mind, pen and paper, and simple observation, evaluation, and judgment. Examiner respectfully disagrees. Taking performance of feature extraction, for example, the broadest reasonable interpretation of this limitation amounts to the transformation of data into a structured format. Such a BRI encompasses calculating the mean, median, standard deviation, correlation and/or covariance, performing component analysis, performing linear discriminant analysis, and so on. Each of these techniques can be performed by hand. Such is the case with the broadest reasonable interpretation of the other elements of the claim, as they are not so narrowly limited to only instances which could not be performed mentally. Applicant’s arguments are therefore unpersuasive.
Applicant argues, on page 11, that the claims do not recite managing personal relationships or behaviors among people. No limitation has been characterized as such.
Applicant argues, on pages 11-12, that the claims do not recite mathematical concepts. Examiner respectfully disagrees, and further reiterates that training a simple linear regression model to make three predictions is within the broadest reasonable interpretation of the claim. Applicant’s arguments are therefore unpersuasive.
Applicant argues, on page 15, that the claims recite additional elements that add something other than that which is well-understood routine and conventional in the art. Examiner respectfully disagrees. Examiner respectfully notes that, but for the requirement to “apply” the abstract idea using a machine learning model, the limitations pointed to by Applicant are part of the abstract idea itself, rather than to any additional elements, and therefore are not considered in determining whether “additional” elements amount to significantly more than the abstract idea.
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 1-15 are rejected under 35 U.S.C. § 101. The claims are drawn to ineligible patent subject matter, because the claims are directed to a recited judicial exception to patentability (an abstract idea), without claiming something significantly more than the judicial exception itself.
Claims are ineligible for patent protection if they are drawn to subject matter which is not within one of the four statutory categories, or, if the subject matter claimed does fall into one of the four statutory categories, the claims are ineligible if they recite a judicial exception, are directed to that judicial exception, and do not recite additional elements which amount to significantly more than the judicial exception itself. Alice Corp. v. CLS Bank Int'l, 375 U.S. ___ (2014). Accordingly, claims are first analyzed to determine whether they fall into one of the four statutory categories of patent eligible subject matter. Then, if the claims fall within one of the four statutory categories, it must be determined whether the claims are directed to a judicial exception to patentability (i.e., a law of nature, a natural phenomenon, or an abstract idea). In determining whether a claim is directed to a judicial exception, the claim is first analyzed to determine whether the claim recites a judicial exception. If the claim does not recite one of these exceptions, the claim is directed to patent eligible subject matter under 35 U.S.C. 101. If the claim recites one of these exceptions, the claim is then analyzed to determine whether the claim recites additional elements that integrate the exception into a practical application of that exception. Claims which integrate the exception into a practical application of that exception are directed to patent eligible subject matter under 35 U.S.C. 101. If the claim fails to integrate the exception into a practical application of that exception, the claim is directed to an abstract idea. Finally, if the claims are directed to a judicial exception to patentability, the claims are then analyzed determine whether the claims are directed to patent eligible subject matter by reciting meaningful limitations which transform the judicial exception into something significantly more than the judicial exception itself. If they do not, the claims are not directed towards eligible subject matter under 35 U.S.C. § 101.
Regarding independent claims 1, 14, and 15 the claims are directed to one of the four statutory categories (a machine, a process, and an article of manufacture, respectively.) The claimed invention of independent claims 1, 14, and 15 is directed to a judicial exception to patentability, an abstract idea. The claims include limitations which recite elements which can be properly characterized under at least one of the following groupings of subject matter recognized as abstract ideas by MPEP 2106.04(a):
Mathematical Concepts: mathematical relationships, mathematical formulas or equations, and mathematical calculations;
Certain methods of organizing human activity: fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
Mental processes: concepts performed in the human mind (including an observation, evaluation, judgment, opinion)
Claims 1, 14, and 15, as a whole, recite the following limitations:
performing feature engineering to contextually enrich collected data; (claims 1, 14, 15; the broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could perform feature engineering to contextually enrich collected data; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial mapping agencies would perform this step in creating insights and visualizations of areas for customers)
generating three datasets from the contextually enriched data, wherein a first dataset is generated by combining positive samples of the contextually enriched collected data with hard negative samples of the contextually enriched data, a second dataset is generated by combining the positive samples with soft negative samples of the contextually enriched data, and a third dataset is generated by combining the positive samples, hard negative samples, and soft negative samples; and (claims 1, 14, 15; the broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could generate these three data sets; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial mapping agencies would perform this step in creating insights and visualizations of areas for customers)
training a machine learning model to generate three different types of predictions for the risk/value assessment of the geographic area based on the three generated datasets. (claims 1, 14, 15; the broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could train a machine learning model on these data sets; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial mapping agencies would perform this step in creating insights and visualizations of areas for customers; further still, the training of machine learning model recites mathematical concepts since it is so broad as to encompass simple linear regression, or other mathematical formulas or operations used to train a model (a loss function, for example).)
The above elements, as a whole, recite mental processes since, but for the requirement to implement the above steps on a set of generic computer components, the entirety of the above set of steps could be performed by a human using their mind, pen and paper, and simple observation, evaluation, and judgment. Furthermore, as a whole, the claims recite certain methods activity since they recite a set of steps for creating insights and visualizations of areas, which comprises certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial mapping agencies would perform this set of steps in creating maps for customers.
Moving forward, the above recited abstract idea is not integrated into a practical application.
The added limitations do not represent an integration of the abstract idea into a practical application because:
the claims represent mere instructions to implement an abstract idea on a computer, and merely use a computer as a tool to perform an abstract idea. See MPEP 2106.05(f).
the claims merely add insignificant extra-solution activity to the judicial exception (activity which can be characterized as incidental to the primary purpose or product that is merely a nominal or tangential addition to the claim). See MPEP 2106.05(g) and/or
the claims represent mere general linking of the use of the judicial exception to a particular technological environment or field of use. See MPEP 2016.05(h)
Beyond those limitations which recite the abstract idea, the following limitations are added:
A computer-implemented method for artificial intelligence (AI) based risk/value assessment of a geographic area, the method comprising: (claim 1; the broadest reasonable interpretation of this limitation represents mere instructions to implement the abstract idea on a generic computer used as a tool in its ordinary capacity; alternatively, the broadest reasonable interpretation of this limitation represents mere general linking of the abstract idea to a particular computer environment or field of use)
A computer system programmed for artificial intelligence (AI) based risk/value assessment of a geographic area, the computer system comprising one or more hardware processors which, alone or in combination, are configured to provide for execution of the following steps: (claim 14; the broadest reasonable interpretation of this limitation represents mere instructions to implement the abstract idea on a generic computer used as a tool in its ordinary capacity; alternatively, the broadest reasonable interpretation of this limitation represents mere general linking of the abstract idea to a particular computer environment or field of use)
A tangible, non-transitory computer-readable medium for artificial intelligence (AI) based risk/value assessment of a geographic area, the computer-readable medium having instructions thereon, which, upon being executed by one or more processors, provides for execution of the following steps: (claim 15; the broadest reasonable interpretation of this limitation represents mere instructions to implement the abstract idea on a generic computer used as a tool in its ordinary capacity; alternatively, the broadest reasonable interpretation of this limitation represents mere general linking of the abstract idea to a particular computer environment or field of use)
training a machine learning model to generate three different types of predictions for the risk/value assessment of the geographic area based on the three generated datasets. (claims 1, 14, 15; the broadest reasonable interpretation of this limitation further amounts to the mere requirement to “apply” the abstract idea using a machine learning model since the training step here is applied at a high level of generality, the mere end result of the training is recited without explaining how the model is trained, and since the information is used to perform an existing model training process)
The claims, as a whole, are directed to the abstract idea(s) which they recite. The claim limitations do not present improvements to another technological field, nor do they improve the functioning of a computer or another technology. Nor do the claim limitations apply the judicial exception with, or by use of a particular machine. The claims do not effect a transformation or reduction of a particular article to a different state or thing. See MPEP 2106.05(c). None of the hardware in the claims "offers a meaningful limitation beyond generally linking 'the use of the [method] to a particular technological environment' that is, implementation via computers” such that the claim as a whole is more than a drafting effort designed to monopolize the exception. See MPEP 2106.05(e); Alice Corp. v. CLS Bank Int’l (citing Bilski v. Kappos, 561 U.S. 610, 611 (U.S. 2010)). Therefore, because the claims recite a judicial exception (an abstract idea) and do not integrate the judicial exception into a practical application, the claims, as a whole, are directed to the judicial exception.
Turning to the final prong of the test (Step 2B), independent claims 1, 14, and 15 do not include additional elements that are sufficient to amount to significantly more than the judicial exception, because there are no meaningful limitations which transform the exception into a patent eligible application.
As outlined above, the claim limitations do not present improvements to another technological field, nor do they improve the functioning of a computer or another technology. Nor do the claim limitations apply the judicial exception with, or by use of a particular machine. The claims do not effect a transformation or reduction of a particular article to a different state or thing. See MPEP 2106.05(c). None of the hardware in the claims "offers a meaningful limitation beyond generally linking 'the use of the [method] to a particular technological environment' that is, implementation via computers” such that the claim as a whole is more than a drafting effort designed to monopolize the exception. See MPEP 2106.05(e); Alice Corp. v. CLS Bank Int’l (citing Bilski v. Kappos, 561 U.S. 610, 611 (U.S. 2010)).
Furthermore, no specific limitations are added which represent something other than what is well-understood, routine, and conventional activity in the field. See MPEP 2106.05(d). Besides performing the abstract idea itself, the generic computer components only serve to perform the court-recognized well-understood computer functions of receiving or transmitting data over a network, performing repetitive calculations, electronic record keeping, and storing and retrieving information in memory. See MPEP 2106.05(d). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. Their collective functions merely provide conventional computer implementation. The specification details any combination of a generic computer system program to perform the method. Generically recited computer elements do not add a meaningful limitation to the abstract idea because they would be routine in any computer implementation and because the Alice decision noted that generic structures that merely apply the abstract ideas are not significantly more than the abstract ideas. Therefore, independent claims 1, 14, and 15 are rejected under 35 U.S.C. §101 as being directed to ineligible subject matter.
Claims 2-13, recite the same abstract idea as their respective independent claims.
The following additional features are added in the dependent claims:
Claim 2:
predicting, using a combination of the three predictions of the machine learning model, the risk/value assessment of the geographic area.
The broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could use a machine learning model in this manner; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial mapping agencies would perform this step in creating insights and visualizations of areas for customers; further still, the training of machine learning model recites mathematical concepts since it is so broad as to encompass any mathematical operation or formula using such a type of machine learning model. Furthermore, the broadest reasonable interpretation of this limitation further amounts to the mere requirement to “apply” the abstract idea using a machine learning model since the model here is applied at a high level of generality, the mere end result of the model is recited without explaining how the model performs its functions, and since the model is used as a tool in its ordinary capacity to perform a prediction.
Claim 3:
generating a heat map using the risk/value assessment of the geographic area.
The broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could generate a heat map using a risk/value assessment of a geographic area; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial mapping agencies would perform this step in creating insights and visualizations of areas for customers.
Claim 4:
wherein the machine learning model is trained to make a first one of the predictions as a country-wide prediction of risk/value using a first model that discriminates the positive samples and the soft negative samples.
The broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could use a machine learning model in this manner; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial mapping agencies would perform this step in creating insights and visualizations of areas for customers; further still, the training of machine learning model recites mathematical concepts since it is so broad as to encompass any mathematical operation or formula using such a type of machine learning model. Furthermore, the broadest reasonable interpretation of this limitation further amounts to the mere requirement to “apply” the abstract idea using a machine learning model since the model here is applied at a high level of generality, the mere end result of the model is recited without explaining how the model performs its functions, and since the model is used as a tool in its ordinary capacity to perform a prediction.
Claim 5:
wherein the machine learning model is trained to make a second one of the predictions as a nearby-area prediction of risk/value using a second model that, given two points of the hard negative samples, discriminates the two points as positive or negative points.
The broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could use a machine learning model in this manner; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial mapping agencies would perform this step in creating insights and visualizations of areas for customers; further still, the training of machine learning model recites mathematical concepts since it is so broad as to encompass any mathematical operation or formula using such a type of machine learning model. Furthermore, the broadest reasonable interpretation of this limitation further amounts to the mere requirement to “apply” the abstract idea using a machine learning model since the model here is applied at a high level of generality, the mere end result of the model is recited without explaining how the model performs its functions, and since the model is used as a tool in its ordinary capacity to perform a prediction.
Claim 6:
wherein the machine learning model is trained to make a third one of the predictions as a study-area prediction using a third model that uses the positive samples, hard negative samples, and soft negative samples to apply to a new and unseen area.
The broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could use a machine learning model in this manner; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial mapping agencies would perform this step in creating insights and visualizations of areas for customers; further still, the training of machine learning model recites mathematical concepts since it is so broad as to encompass any mathematical operation or formula using such a type of machine learning model. Furthermore, the broadest reasonable interpretation of this limitation further amounts to the mere requirement to “apply” the abstract idea using a machine learning model since the model here is applied at a high level of generality, the mere end result of the model is recited without explaining how the model performs its functions, and since the model is used as a tool in its ordinary capacity to perform a prediction.
Claim 7:
gathering data of heterogeneous types from a selected geographic area;
semantically mapping the gathered data to a backbone ontology associated with the selected geographic area using annotations, wherein the backbone ontology is generated by merging multiple ontologies; and
converting the mapped gathered data into a standard data format.
The broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could gather data, semantically map it, and convert it into a standard format; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial mapping agencies would perform this step in creating insights and visualizations of areas for customers
Claim 8:
wherein the feature engineering comprises mapping the collected data to information in a contextual database,
wherein performing feature engineering to contextually enrich the collected data comprises mapping the collected data with a first set of explanatory variables calculated from the contextual database, and
wherein the first set of explanatory variables are based on geographical features stored in the contextual database.
The broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could map data into a database in this manner; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial mapping agencies would perform this step in creating insights and visualizations of areas for customers. Regarding the use of a database, the broadest reasonable interpretation of this limitation represents mere instructions to implement the abstract idea on a generic computer used as a tool in its ordinary capacity; alternatively, the broadest reasonable interpretation of this limitation represents mere general linking of the abstract idea to a particular computer environment or field of use.
Claim 9:
wherein performing feature engineering to contextually enrich the collected data further comprises mapping the collected data with a second set of explanatory variables calculated from the contextual database, wherein the second set of explanatory variables are based on distances to key facilities and infrastructure.
The broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could map collected data with explanatory variables of this type in this manner; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial mapping agencies would perform this step in creating insights and visualizations of areas for customers.
Claim 10:
wherein the positive samples of collected data comprise randomly selected points within the geographic area, and/or wherein the positive samples are equally selected from different polygon areas.
The broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could collect and use samples of this type in the abstract idea above; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial mapping agencies would perform this step in creating insights and visualizations of areas for customers.
Claim 11:
wherein the hard negative samples of collected data comprise sampled points from within a selectable buffer distance around the geographic area, wherein the sampled points indicate an absence of a geographic hazard.
The broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could collect and use samples of this type in the abstract idea above; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial mapping agencies would perform this step in creating insights and visualizations of areas for customers.
Claim 12:
wherein the hard negative samples are a subset of a plurality of sampled points, wherein the subset of the plurality of sampled points is selected based a similarity value, and wherein the similarity value is calculated based on comparing geographical features of the sampled points with geographical features of the positive samples.
The broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could collect and use samples of this type in the abstract idea above; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial mapping agencies would perform this step in creating insights and visualizations of areas for customers.
Claim 13:
wherein the soft negative samples of the collected data comprise points sampled from within a country of which the geographic area is a part, wherein the sampled points indicate an absence of a geographic hazard.
The broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could collect and use samples of this type in the abstract idea above; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial mapping agencies would perform this step in creating insights and visualizations of areas for customers.
The above limitations do not represent a practical application of the recited abstract idea. The claim limitations do not present improvements to another technological field, nor do they improve the functioning of a computer or another technology. Nor do the claim limitations apply the judicial exception with, or by use of a particular machine. The claims do not effect a transformation or reduction of a particular article to a different state or thing. See MPEP 2106.05(c). None of the hardware in the claims "offers a meaningful limitation beyond generally linking 'the use of the [method] to a particular technological environment' that is, implementation via computers” such that the claim as a whole is more than a drafting effort designed to monopolize the exception. See MPEP 2106.05(e); Alice Corp. v. CLS Bank Int’l (citing Bilski v. Kappos, 561 U.S. 610, 611 (U.S. 2010)). Therefore, because the claims recite a judicial exception (an abstract idea) and do not integrate the judicial exception into a practical application, the claims are also directed to the judicial exception.
Furthermore, the added limitations do not direct the claim to significantly more than the abstract idea. No specific limitations are added which represent something other than what is well-understood, routine, and conventional activity in the field. See MPEP 2106.05(d). Accordingly, none of the dependent claims 2-13, individually, or as an ordered combination, are directed to patent eligible subject matter under 35 U.S.C. 101.
Please see MPEP §2106.05(d)(II) for a discussion of elements that the Courts have recognized as well-understood, routine, conventional, activity in particular fields.
Please see MPEP §2106 for examination guidelines regarding patent subject matter eligibility.
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 EMMETT K WALSH whose telephone number is (571)272-2624. The examiner can normally be reached Mon.-Fri. 6 a.m. - 4:45 p.m..
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/EMMETT K. WALSH/Primary Examiner, Art Unit 3628
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