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 .
This office action is in response to communication filed on 12/2/2025.
Claims 2-3 and 5 have been cancelled. Claims 1, 4 and 6 are presented for examination.
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, 4 and 6 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Determining that a claim falls within one of the four enumerated categories of patentable subject matter recited in 35 U.S.C. 101 (i.e., process, machine, manufacture, or composition of matter). (MPEP 2106.03)
Claims 1 and 4 describe tangible system components, thus falling within one of the statutory classes; i.e. machine. Claim 6 describes a series of steps, thus falling within one of the four statutory classes; i.e. process.
Step 2A, Prong One: Evaluating whether the claim(s) recite(s) a judicial exception, i.e. whether a law of nature, natural phenomenon, or abstract idea is set forth or described in the claim. (MPEP 2106.04).
Representative claim 6 recites:
acquiring user information related to a user to be provided with a recommendation;
determining content to be recommended to the user on the basis of at least a part of the acquired user information that includes at least a detected current location of the user, the determined content being a store that is within a predetermined range of the current location of the terminal device;
determining an expression configured to affect a behavior of the user when the determined content is recommended to the user on the basis of at least a part of the acquired user information; acquiring difficulty information indicating a degree of difficulty with which the user adopts a behavior with respect to the determined content;
acquiring behavior information indicating a behavior of the user with respect to a recommendation provided to the user according to determination;
a recommendation expression determination method in consideration of the degree of difficulty with which the user to be provided with a recommendation adopts a behavior on the basis of the acquired difficulty information and the acquired behavior information; and
triggering providing the recommendation to the user via the terminal device when the user enters a specific area based on the detected current location of the user,
weighting an evaluation value based on the behavior information on the basis of the difficulty information and performs the recommendation expression determination method using the weighted evaluation value, and
determining the expression based on a psychological bias of the user that is estimated by a psychological bias estimation model.
The claim pertains to: weighting an evaluation value based on the behavior information on the basis of the difficulty information and performs the recommendation expression determination method using the weighted evaluation value. The limitations under their broadest reasonable interpretation covers managing personal behavior and fall under “Certain Methods of Organizing Human activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A, Prong Two: Identifying whether there are any additional elements recited in the claim beyond the judicial exception(s); and then evaluating those additional elements individually and in combination to determine whether they integrate the exception into a practical application. Prong Two distinguishes claims that are "directed to" the recited judicial exception from claims that are not "directed to" the recited judicial exception. (MPEP 2106.04).
This judicial exception is not integrated into a practical application. In particular, the claims recite the following additional elements:
• one or more circuitry (claims 1 and 6)
Machine learning (claims 1 and 6)
The additional elements of a circuitry and machine learning for recommendations and determining expression based on a physiological traits of the user are considered as “apply it” as the claim invokes the computer as a tool to perform the abstract idea. See MPEP 2106.05(f)(2) (similar to Apple, Inc. v Ameranth and Intellectual Ventures I LLC v Capital One Bank (USA).
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. (MPEP 2106.05(f) Mere Instructions To Apply An Exception).
Regarding the limitation “a recommendation system comprising a circuitry”, and machine learning as seen above, are limitations that have been interpreted as “apply it”. However, these limitations can be additionally interpreted as insignificant extra-solution activity. As such, these limitations alone and in combination, do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. (MPEP 2106.05(g) Insignificant Extra-Solution Activity).
Therefore, under Step 2A, Prong Two, the claims are directed to an abstract idea.
Step 2B: Identifying whether there are any additional elements (features/limitations/steps) recited in the claim beyond the judicial exception(s), and then evaluating those additional elements individually and in combination to determine whether they contribute an inventive concept (i.e., amount to significantly more than the judicial exception(s)). (MPEP 2106.05)
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Therefore, claims 1, 4 and 6 are patent eligible.
Allowable Subject Matter
Claims 1, 4 and 6 are allowable over prior art of record.
The closest prior art of record Miao (JP 2021-149929) is directed to a content recommendation method that includes obtaining candidate contents to be recommended and at least one user feature tag for the user; determining a recommendation scheme according to the candidate contents and the at least one user feature tag, including respective proportions of different types of candidate contents in N pieces of recommended contents recommended to the user, the N pieces of recommended contents selected from the candidate contents according to the proportions, and an order of displaying the recommended contents in the N pieces of recommended contents, N is a positive integer greater than one and less than or equal to the number of candidate contents; and returning the recommended contents to the user according to the recommendation scheme. (See abstract).
Miao does not disclose determining expression for recommending content to a user pertaining to a degree of difficulty with which a user adopts a behavior with respect to the content determined to be recommended to the user, as in the present invention.
O’Donnell (2003/0027116) teaches “a method for assisting a person in changing a behavior….. a) having the person assess, on a quantitative scale, the degree of his readiness to change; b) having the person assess, on a quantitative scale, the difficulty of changing said behavior… and on paragraph 0028 “in step 4,…. Difficulty is rated on a 1-4”. Nevertheless, O’Donnell does not relate to content recommendations to a user pertaining to a degree of difficulty with which a user adopts a behavior with respect to the content determined to be recommended to the user, as in the present invention.
Article from Wikipedia, the free encyclopedia titled “Psychographic” teaches psychographic profiles that are used in market segmentation as well as in advertising. Some categories of psychographic factors used in market segmentation include: activity, interest, opinion (AIOs), attitudes, and lifestyles. Nevertheless, it doesn’t relate to content recommendations to a user pertaining to a degree of difficulty with which a user adopts a behavior with respect to the content determined to be recommended to the user, as in the present invention.
Response to Arguments
The claims amendments overcame the 112(b) rejections.
Applicant argues that the claims technical features make it clear that the claims as a whole cannot be interpreted as a method of organizing a human activity. The Examiner disagrees with Applicant because the claims pertain to: weighting an evaluation value based on the behavior information on the basis of the difficulty information and performs the recommendation expression determination method using the weighted evaluation value. The limitations under their broadest reasonable interpretation covers managing personal behavior and fall under “Certain Methods of Organizing Human activity” grouping of abstract ideas. The claims further recite the additional elements of learning machine weights the calculated behavior modification evaluation value on the basis of behavior difficulty as disclosed on specification as filed on paragraph 0078, but it doesn’t disclose the algorithm/steps on how the machine is trained and learns and therefore is considered as “apply it”, “field of use”, as the claims involve the computer as a tool to perform the abstract idea, and not how the machine is trained and is not significantly more, under step 2A, prong two.
The claims in Ex Parte Guillaume Desjardins pertained to a practical application because the invention improved how the machine learning model operated, including reducing storage requirements and system complexity, the improvements were analogous to a technological improvement in computer functionality (similar to Enfish) which can support patent eligibility, which is not the case in the present claims which do not disclose the algorithms, steps by steps how the machine learning model operates/learns, or how it improves a computer functionality.
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.
Point of contact
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RAQUEL ALVAREZ whose telephone number is (571)272-6715. The examiner can normally be reached Mondays thru Thursdays 8:30-6:30.
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/RAQUEL ALVAREZ/Primary Examiner, Art Unit 3622