DETAILED ACTION
This office action is in response to communication filed on 11 March 2026.
Claims 1, 2, 8 – 15, 17 – 19, and 21 are presented for examination.
The following is a FINAL office action upon examination of application number 18/376278. Claims 1, 2, 8 – 15, 17 – 19, and 21 are pending in the application and have been examined on the merits discussed below.
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 Amendment
In the response filed 11 March 2026, Applicant amended claims 1, 8, 11, and 19. Applicant cancelled claims 3 – 7, 16, and 20 and added claim 21.
Amendments to claims 1, 8, 11, and 19 are insufficient to overcome the 35 USC § 101 rejection. Therefore, the 35 USC § 101 rejection of claims 1, 2, 8 – 15, 17 – 19, and 21 are maintained.
Response to Arguments
Applicant's arguments filed 11 March 2026 have been fully considered but they are not persuasive.
In the remarks regarding the 35 USC 101 rejection, Applicant argues that claims describe a practical application. Examiner respectfully disagrees. Utilizing a rationalization model and making determinations for which questions are most likely to distinguish a disposition recommendation from another by utilizing disposition probabilities is entirely abstract without requirement for any technology. There is no practical application, just an “apply it” of using generic technology applied to entirely abstract function. Applicant’s description of determining probabilities greater than others by a threshold amount ending a survey, or changing number of questions are all further detail into the abstract idea. These functions can and are performed by human beings without technology present. The addition of technology that is not required does not raise the claims to the level of significantly more. The 35 USC 101 rejection is proper and maintained.
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, 2, 8 – 15, 17 – 19, and 21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to the judicial exception of abstract ideas without significantly more. The independent claims recite administering an introductory question set to a stakeholder, wherein the introductory question set is selected from a plurality of questions of the survey; collecting response data from the introductory question set; determining, using a rationalization model, a plurality of disposition probabilities based on response data from the introductory question set, wherein each disposition probability of the plurality of disposition probabilities is representative of a predicted likelihood of occurrence of a disposition recommendation, the disposition recommendation selected from a plurality of disposition recommendations and wherein the rationalization model includes a plurality of weights determined during training of the rationalization model, each weight of the plurality of weights associated with one of the plurality of questions, and wherein question importance is assigned in order of decreasing weight associated with each question, and wherein the introductory question set contains questions with higher question importance than any additional question; determining a probability difference between the highest probability and the second-highest probability among the plurality of disposition probabilities; comparing the probability difference to a probability difference threshold; ending the survey at a second number of questions that is less than the first number of questions upon determining that the probability difference is equal to or greater than the probability difference threshold; and administering an additional question upon determining the probability difference is less than the probability difference threshold, wherein the additional question is selected from the plurality of questions based a descending order of question importance; and output a disposition recommendation corresponding to a maximum disposition probability of the plurality of disposition probabilities upon determining the probability difference is equal to or greater than the probability difference threshold. This judicial exception is not integrated into a practical application. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The eligibility analysis in support of these findings is provided below, in accordance section 2106 of the MPEP (hereinafter, MPEP 2106).
With respect to Step 1 of the eligibility inquiry (as explained in MPEP 2106), it is noted that the method and the computing devices are directed to an eligible categories of subject matter. Step 1 is satisfied.
With respect to Step 2A prong 1 of MPEP 2106, it is next noted that the claims recite an abstract idea by reciting concepts of administering a survey and ending a survey at a set number of questions, which falls into the “certain methods of organizing human activity” group within the enumerated groupings of abstract ideas set forth in the MPEP 2106. The claimed invention also recites an abstract idea that falls within the mental processes grouping. Collecting data, determining probabilities, determining probability differences, and comparing probability differences are all functions that can be performed within the human mind. The limitations reciting the abstract idea in independent claims are administering an introductory question set to a stakeholder, wherein the introductory question set is selected from a plurality of questions of the survey; collecting response data from the introductory question set; determining, using a rationalization model, a plurality of disposition probabilities based on response data from the introductory question set, wherein each disposition probability of the plurality of disposition probabilities is representative of a predicted likelihood of occurrence of a disposition recommendation, the disposition recommendation selected from a plurality of disposition recommendations and wherein the rationalization model includes a plurality of weights determined during training of the rationalization model, each weight of the plurality of weights associated with one of the plurality of questions, and wherein question importance is assigned in order of decreasing weight associated with each question, and wherein the introductory question set contains questions with higher question importance than any additional question; determining a probability difference between the highest probability and the second-highest probability among the plurality of disposition probabilities; comparing the probability difference to a probability difference threshold; ending the survey at a second number of questions that is less than the first number of questions upon determining that the probability difference is equal to or greater than the probability difference threshold; and administering an additional question upon determining the probability difference is less than the probability difference threshold, wherein the additional question is selected from the plurality of questions based a descending order of question importance; and output a disposition recommendation corresponding to a maximum disposition probability of the plurality of disposition probabilities upon determining the probability difference is equal to or greater than the probability difference threshold.
With respect to Step 2A Prong Two of the MPEP 2106, the judicial exception is not integrated into a practical application. The additional elements are directed to a computing device, user interface, machine learning models, processors, and computer-readable memory, to implement the abstract idea. However, these elements fail to integrate the abstract idea into a practical application because they are directed to the use of generic computing elements to perform the abstract idea, which is not sufficient to amount to a practical application (as noted in the MPEP 2106) and is tantamount to simply saying “apply it” using a general purpose computer, which merely serves to tie the abstract idea to a particular technological environment by using the computer as a tool to perform the abstract idea, which is not sufficient to amount to particular application.
Accordingly, because the Step 2A Prong One and Prong Two analysis resulted in the conclusion that the claims are directed to an abstract idea, additional analysis under Step 2B of the eligibility inquiry must be conducted in order to determine whether any claim element or combination of elements amount to significantly more than the judicial exception.
With respect to Step 2B of the eligibility inquiry, it has been determined that the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional limitations are directed to: a computing device, user interface, machine learning models, processors, and computer-readable memory. These elements have been considered, but merely serve to tie the invention to a particular operating environment, though at a very high level of generality and without imposing meaningful limitation on the scope of the claim. This does not amount to significantly more than the abstract idea, and it is not enough to transform an abstract idea into eligible subject matter. Such generic, high-level, and nominal involvement of a computer or computer-based elements for carrying out the invention merely serves to tie the abstract idea to a particular technological environment, which is not enough to render the claims patent-eligible, as noted at pg. 74624 of Federal Register/Vol. 79, No. 241, citing Alice, which in turn cites Mayo.
In addition, when taken as an ordered combination, the ordered combination adds nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements integrates the abstract idea into a practical application. Their collective functions merely provide conventional computer implementation. Therefore, when viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a practical application of the abstract idea or that the ordered combination amounts to significantly more than the abstract idea itself.
The dependent claims have been fully considered as well, however, similar to the finding for claims above, these claims are similarly directed to the abstract idea of concepts of determining further probabilities and administering further questions, by way of examples, without integrating it into a practical application and with, at most, a general purpose computer that serves to tie the idea to a particular technological environment, which does not add significantly more to the claims. The ordered combination of elements in the dependent claims (including the limitations inherited from the parent claim(s)) add nothing that is not already present as when the elements are taken individually. 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. Accordingly, the subject matter encompassed by the dependent claims fails to amount to significantly more than the abstract idea.
Allowable Subject Matter
Claims 1, 2, 8 – 15, 17 – 19, and 21 would be allowable if rewritten or amended to overcome the rejection under 35 U.S.C. 101 set forth in this Office action.
The following is a statement of reasons for the indication of allowable subject matter: None of the prior art of record, taken individually or in any combination, teach, inter alia to administer an introductory question set to a stakeholder via a user interface, wherein the introductory question set is selected from a plurality of questions of the survey; collect response data from the introductory question set; determine, using a rationalization model comprising one or more machine learning models, a plurality of disposition probabilities based on response data from the introductory question set, wherein each disposition probability of the plurality of disposition probabilities is representative of a predicted likelihood of occurrence of a disposition recommendation, the disposition recommendation selected from a plurality of disposition recommendations; determine a probability difference based on two disposition probabilities of the plurality of disposition probabilities; compare the probability difference to a probability difference threshold; and end the survey at a second number of questions that is less than the first number of questions upon determining that the probability difference is equal to or greater than the probability difference threshold.
The closest prior art of Sachdev (U.S. P.G. Pub. 2017/0270432) discloses system modernization (including application rationalization) while providing recommendations with questionnaires without calculating any probabilities. Gantait (U.S. P.G. Pub. 2019/0266539) teaches automated rationalization for software applications and determining recommendations, but does not disclose any probability calculation. Jayarama (U.S. P.G. Pub. 2019/0102682) discloses machine learning for probabilities of categorizing test data with confidence thresholds. Garland (U.S. P.G. Pub. 2013/0054497) discloses determining satisfaction in surveys including probability that is the case with thresholds, but no comparison of the probabilities. Bijani (U.S. P.G. Pub. 2019/0026085) discloses recommendations for service categories of applications utilizing artificial intelligence. However, none of these taken individually or in combination teach the particular method of an introductory question set of a survey with responses, then using a rationalization model with machine learning to determine disposition probabilities representative of predicted likelihood of a disposition recommendation, determining a probability difference between two and comparing the difference to a threshold, and ending the survey at a number of questions upon determining the probability difference is equal or greater than the difference threshold, as claimed herein. Furthermore, neither the prior art, the nature of the problem, not knowledge of a person having ordinary skill in the art provides for any predictable or reasonable rationale to combine prior art teachings.
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.
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/AMANDA GURSKI/Primary Examiner, Art Unit 3625