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 .
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite a mathematical concept including predicting a clickstream metric, determining an anomaly based on the measured metric falling outside a predicted range, predicting probability levels corresponding to anomaly types and determining an anomaly type corresponding to the highest probability level. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application because the claim recites a processor and memory which are recited at a high-level of generality (i.e., as a generic processor performing a generic computer functions) such that it amounts no more than mere instructions to apply the exception using a generic computer component. The ML model is recited generically with no particular architecture and merely applies the abstract idea in a particular environment. Identifying clickstream data is an extra solution data gathering step, limiting the claim to websites and clickstream data is a field of use limitation. The claim does not recite any action taken in response to the determined anomaly type or any improvement to the computer functionality.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional element of are generic computer components perform their ordinary computing functions, while obtaining clickstream data constitutes data gathering for use in the recited analysis. The ML model is recited at a high level of generality and does not have a particular architecture or technological improvement. The additional elements amount to implementing the recited analysis in a computer based website environment. The claim as a whole does not recite significantly more than the judicial exception. Claims 1, 8 and 15 are not patent eligible.
Dependent claims 2-7, 9-14 and 18-20 only further limitations to the abstract idea in the independent claims (data gathering, classification) or insignificant extra-solution activity. They do not integrate the abstract idea into practical application or add significantly more than the judicial exception. As such claims are still directed to an abstract idea.
Response to Arguments
Applicant's arguments filed 7/6/2026 have been fully considered but they are not persuasive.
Applicant states:
Applicant respectfully submits that even if one believed that claim 1, as alleged by the Office Action, "recites steps" relating in some way to "collecting, analyzing and classifying information," claim 1 as amended still does not recite a "mental process." Claim 1 is not directed toward the abstract steps of "collecting, analyzing and classifying information." Instead, claim 1 as amended is directed toward "A system" that can "determine an anomaly website event for an interaction of the client device with the website based on a measurement of the clickstream metric failing to reach a predefined range of the predicted clickstream metric," "predict, using at least a machine learning model and the clickstream data, a set of probability levels corresponding to [a] set of anomaly types," and "determine an anomaly type for the anomaly website event based at least in part on the anomaly type corresponding to a highest probability level in the set of probability levels." Applicant respectfully submits that this language is technically grounded language and does not attempt to claim or preempt any abstract idea or "mental process."
Examiner respectfully disagrees. Applicant’s amended claim machine learning model recites an abstract idea in the form of a mathematical analysis. Independent claims recite predicating a set of probability levels corresponding to a set of anomaly types and determining an anomaly type based on the anomaly type corresponding to a highest probability level in the set of probability levels. The specification further describe the prediction and anomaly determination using mathematical calculations (¶0058-¶0061). Implementing the analysis using a ML model and clickstream data does not integrate the judicial exception into a practical application. The claim does not recite a specific improvement to the ML model, computer functionality or technology.
Applicant states:
Applicant also notes, in regard to allegations that claim 1 recites a "mathematical relationship," that no specific example of a "mathematical relationship" has been identified in claim 1. Even as the Office Action claims that the "absence of mathematical equations does not remove the claim from the abstract idea category," Applicant submits that some language in claim 1 must recite a "mathematical relationship" for the claim to be directed towards the corresponding abstract idea. (Office Action, p. 4). The Office Action alleges that "the claims still recite evaluation, prediction and classification of information," but these are not "mathematical relationships." Id. As Applicant has previously cited, "training the neural network in a first stage using the first training set" does not recite a "mathematical relationship" under the USPTO's guidance, even though the language "involves a broad array of techniques and/or activities that may involve or rely upon mathematical concepts." USPTO, Reminders on evaluating subject matter eligibility of claims under 35 U.S.C. 101, p. 3, (published August 4, 2025) (last accessed July 5, 2026) (available at https://www.uspto.gov/sites/default/files/documents/memo-101- 20250804.pdf). Applicant respectfully submits that, similarly, claim 1 does not recite a "mathematical relationship," even if the claim is broadly alleged by the Office Action to involve "evaluation, prediction and classification of information."
Examiner respectfully disagrees. Claim 1 requires predicting a set of probability levels corresponding to a set of anomaly types and determining the anomaly type corresponding to the highest probability level. In light of the specification these limitations encompass mathematical calculations used to determine and compare numerical probability values. The claim requires comparing probability levels when determining an anomaly type.
Applicant states:
That "predict, using at least a machine learning model and the clickstream data, a set of probability levels corresponding to the set of anomaly types" and "determine an anomaly type for the anomaly website event based at least in part on the anomaly type corresponding to a highest probability level in the set of probability levels" are closely related to the "technical solution" described and therefore integrate the alleged judicial exception into a practical application.
Examiner respectfully disagrees. The claim recites predict, using at least a machine learning model and the clickstream data, a set of probability levels corresponding to the set of anomaly types; and determine an anomaly type for the anomaly website event based at least in part on the anomaly type corresponding to a highest probability level in the set of probability levels. The claim does not recite using the determined anomaly type to implement an improvement in the functioning of the computer or website itself. The amended limitations do not integrate the judicial exception into a practical application.
Applicant states:
Applicant respectfully submits that claims 1-20 contain language that is not "well- understood" or "routine" for the relevant "industry." For example, claim 1 recites "predict, using at least a machine learning model and the clickstream data, a set of probability levels corresponding to the set of anomaly types" and "determine an anomaly type for the anomaly website event based at least in part on the anomaly type corresponding to a highest probability level in the set of probability levels." Applicant submits that in the surrounding industry, none of this language is "conventional activity" and instead represents an "inventive concept" and "significantly more" than the alleged judicial exception.
Examiner respectfully disagrees. The use of a machine learning model to predict probability levels for respective anomaly types are part of the abstract analysis itself and cannot represent the significantly more required at step 2B. The additional elements including the process, memory and clickstream data perform the recited analysis using generic computer components and data gathering activity. Considered individually or combined these additional element do not transform the judicial exception.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHARLES EHNE whose telephone number is (571)272-2471. The examiner can normally be reached 8:00-5:00 M-F.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Bryce Bonzo can be reached at 571-272-3655. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/CHARLES EHNE/Primary Examiner, Art Unit 2113
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