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 .
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 1/8/2026 has been entered.
Claims Status
Claims 7-8 and 15-20 have been cancelled.
Claims 1-6 and 9-14 remain pending and stand rejected.
Response to Arguments
I. Applicant’s arguments made with respect to the rejection under 35 USC 101 have been fully considered but are not persuasive.
Applicant’s arguments center on the problem of data scarcity or sparse data. Initially, the Examiner asserts that this problem exists outside the realm of machine learning, and pertains to the problem of insufficient data in relation to the requirements of any system or process. That is, lack of data is a factor across a myriad of fields of endeavor and is not relegated specifically to technology.
Secondly, The Examiner acknowledges that the problem of data scarcity is noted in the specification (e.g., 0057 (sparse training data), 0061 (small data size), 0063 (learning approaches are “data-hungry”)); however, the manner in which this problem is addressed lacks sufficient detail to demonstrate to one of ordinary skill that the invention achieves an improvement.
As discussed in the Final Action mailed 10/23/2025, if it is asserted that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes, a technical explanation as to how to implement the invention should be present in the specification. That is, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. Although the specification need not explicitly set forth the improvement, it must describe the invention such that the improvement would be apparent to one of ordinary skill in the art. Conversely, if the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology (see MPEP 2106.05(a); MPEP 2106.04(d)(1)).
Applicant’s specification does not provide the requisite detail necessary such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. In 0057, the specification provides a high-level statement that “assuming sparse training data, the preference monitoring and intervention system 500 may train the learning model as a one-vs-rest support vector” sans further detail regarding any specific manner of training other than utilizing an undisclosed manner of training. While “one-vs-rest” models are known in the industry, Applicant’s disclosure does not provide sufficient evidence of a particular manner of training using an OVR model that results in an improved training process for reduced data sets (i.e., sparse data).
Similar analysis with respect to paragraph 0061 is applicable, which states “Another configuration uses an SVM to implement the models for the factor prediction and the intervention prediction of blocks 510 and 520 with a small dataset size. To handle the multi-label classification task, a one-vs-rest model was used for each of the 18 barriers.”. Here again, the OVR model is merely referenced without details of how to implement the OVR in a particular manner to address the “small data set”.
Lastly, paragraph 0063 discusses learning approaches that are “data hungry”, but solves this problem by “an initial data-gathering survey to inform simulation models”. Notably, this is performed in relation to the reinforcement learning model, rather than the factor prediction model (which is trained using the OVR model).
An important consideration in determining whether a claim improves technology is the extent to which the claim covers a particular solution to a problem or a particular way to achieve a desired outcome, as opposed to merely claiming the idea of a solution or outcome (MPEP 2106.05(a)). Furthermore, MPEP 2106.05(f)(1) warns that 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. In the case of the current application, neither the claims nor the specification go beyond the idea of a solution or outcome because they fail to provide sufficient details for how the result is accomplished.
Lastly, even if the specification is understood as explicitly setting forth an improvement, it does so only in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art). Lastly, claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. Accordingly, Applicant’s arguments are found unpersuasive.
II. Applicant’s arguments made with respect to the rejection under 35 USC 103 have ben fully considered and are persuasive in view of the amendment filed 12/10/2025. Applicant has incorporated subject matter previously allowable over the prior art. The rejections are withdrawn.
Claim Rejections - 35 USC § 112(b)
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 1-6 and 9-14 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.
Regarding claim 1 and parallel claim 9, claim 1 recites “updating the selected, pretrained reinforcement learning model based on a measured preference shift of the user in response to the presented intervention”. Prior to this limitation the claim recites both “a highest-ranked intervention” and “a next highest-ranked intervention”. It is unclear which of these two interventions the presented intervention refers back to.
For examination purposes, the claim will be interpreted as the presented interventions, thus requiring updating based on both the preceding interventions.
Claims 5-6 and 10-14 depend from independent claims 1 and 9, respectively, and are rejected therewith.
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 1-6 and 9-14 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (abstract idea) without significantly more.
Regarding claims 1-6 and 9-14, under Step 2A claims 1-6 and 8-14 recite a judicial exception (abstract idea) that is not integrated into a practical application and does not provide significantly more.
Under Step 2A (prong 1), and taking claim 9 as representative, claim 9 recites use of elicited factors to inform intervention suggestions, including
identify a user profile corresponding to a demographic of a user according to a background of the user;
predict factors including an associated set of barriers and/or motivators regarding a respective preference associated with the identified user profile;
predict a plurality of interventions associated with the identified user profile to shift a preference of the user;
present a highest-ranked intervention corresponding to a selected highest-ranked barrier to the user;
present a next highest-ranked intervention corresponding to a selected next highest- ranked barrier; and
repeating the selecting, presenting, and updating until a score threshold, or a maximum number of interventions is reached.
These limitations recite organizing human activity, such as by Managing Personal Behavior or Relationships or Interactions Between People (see: MPEP 2106.04(a)(2)(II)). This is because the claimed invention sets forth and/or describes the use of elicited factors to inform intervention suggestions in order to shift preferences of a user based on information about that user. Accordingly, under step 2A (prong 1) claim 9 recites an abstract idea because claim 9 recites limitations that fall within the “Certain methods of organizing human activity” grouping of abstract ideas.
Under Step 2A (prong 2), the abstract idea is not integrated into a practical application. The Examiner acknowledges that representative claim 9 does recite additional elements including a non-transitory computer-readable medium having program code recorded thereon, the program code being executed by a processor and various program code to limitations (e.g., program code to identify, predict, present, etc.),
program code to train a factor prediction model to perform a multilabel classification task using a one- vs-rest model for each barrier of a predetermined number of barriers based on a reduced dataset
a factor prediction model,
a selected, pretrained reinforcement learning model,
a user device,
a server computer, and,
program code to update the selected, pretrained reinforcement learning model based on a measured preference shift of the user in response to the presented intervention.
Although reciting these additional elements, taken alone or in combination these elements are not sufficient to integrate the abstract idea into a practical application. This is because the additional elements of claim 9 are recited at a high level of generality (i.e. as generic computing hardware) such that they amount to nothing more than the mere instructions to implement or apply the abstract idea on generic computing hardware (or, merely uses a computer as a tool to perform an abstract idea). Lastly, the additional elements do no more than generally link the use of a judicial exception to a particular technological environment or field of use (such as the Internet or computing networks).
In addition to the above, the additional elements are insufficient to integrate the abstract idea into a practical application because the claim fails to (i) reflect an improvement in the functioning of a computer, or an improvement to other technology or technical field, (ii) implement the judicial exception with, or use the judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, (iii) effect a transformation or reduction of a particular article to a different state or thing, or (iv) applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
In view of the above, under Step 2A (prong 2), claim 9 does not integrate the recited exception into a practical application.
Under Step 2B, examiners should evaluate additional elements individually and in combination to determine whether they provide an inventive concept (i.e., whether the additional elements amount to significantly more than the exception itself). In this case, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Returning to representative claim 9, taken individually or as a whole the additional elements of claim 9 do not provide an inventive concept (i.e. they do not amount to “significantly more” than the exception itself). As discussed above with respect to the integration of the abstract idea into a practical application (step 2A (prong 2)), the additional elements used to perform the claimed process amount to no more than the mere instructions to apply the exception using a generic computer and/or no more than a general link to a technological environment.
Furthermore, the additional elements fail to provide significantly more also because the claim simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception. For example, the additional elements of claim 9 utilize operations the courts have held to be well-understood, routine, and conventional (see: MPEP 2106.05(d)(II)), including at least:
receiving or transmitting data over a network,
performing repetitive calculations, and/or
presenting offers
Even considered as an ordered combination (as a whole), the additional elements of claim 9 do not add anything further than when they are considered individually.
In view of the above, representative claim 9 does not provide an inventive concept (“significantly more”) under Step 2B, and is therefore ineligible for patenting.
Regarding dependent claims 10-14, dependent claims 10-14 recite more complexities descriptive of the abstract idea itself, and at least inherit the abstract idea of claim 9. As such, claims 10-14 are understood to recite an abstract idea under step 2A (prong 1) for at least similar reasons as discussed above.
Under prong 2 of step 2A, the additional elements of dependent claims 10-14 also do not integrate the abstract idea into a practical application, considered both individually or as a whole. More specifically, claims 10-14 recite further “program code to” elements. As with claim 9, these elements are recited only at a high level of generality (i.e. as generic computing hardware) such that they amount to nothing more than the mere instructions to implement or apply the abstract idea on generic computing hardware (or, merely uses a computer as a tool to perform an abstract idea). This is especially noteworthy with respect to claim 11, which do little more than recite the use of generic computing components in training (claim 11) in support of the abstract process as discussed previously.
Further, the additional elements do no more than generally link the use of a judicial exception to a particular technological environment or field of use (such as the Internet or computing networks).
Lastly, under step 2B, claims 10-14 also fail to result in “significantly more” than the abstract idea under step 2B. This is again because the claims merely apply the exception on generic computing hardware, generally link the exception to a technological environment, and append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception.
Even when viewed as an ordered combination (as a whole), the additional elements of the dependent claims do not add anything further than when they are considered individually.
In view of the above, claims 10-14 and 16 do not provide an inventive concept (“significantly more”) under Step 2B, and are therefore ineligible for patenting.
Regarding claims 1-6 (method), claims 1-6 recite at least substantially similar concepts and elements as recited in claims 9-14 such that similar analysis of the claims would be readily apparent to one of ordinary skill in the art. Accordingly, claims 1-6 are rejected under at least similar rationale as discussed above concerning claims 9-14.
Subject Matter Allowable Over the Prior Art
Although claims 1-6 and 9-14 remain rejected on other grounds, these claims are allowable over the prior art. This is because Applicant has amended to include the subject matter from claims 8 and 16, which were previously indicated as allowable.
The Examiner hereby asserts that the totality of the evidence neither anticipates nor renders obvious the particular combination of elements as claimed above. That is, the Examiner emphasizes the claims as a whole and hereby asserts that the totality of the evidence fails to set forth, either explicitly or implicitly, an appropriate rationale for combining or otherwise modifying the available prior art to arrive at the claimed invention. The combination of features as claimed would not have been obvious to one of ordinary skill in the art because any combination of the evidence at hand to reach the combination of features as claimed would require a substantial reconstruction of Applicant’s claimed invention relying on improper hindsight bias.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
PTO form 892-U discusses factors for early adoption of electric vehicles (see: abstract).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WILLIAM J ALLEN whose telephone number is (571)272-1443. The examiner can normally be reached Monday-Friday, 8:00-4:00.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Anita Coupe can be reached at 571-270-3614. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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WILLIAM J. ALLEN
Primary Examiner
Art Unit 3625
/WILLIAM J ALLEN/ Primary Examiner, Art Unit 3619