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 § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-5, 9-15, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Grizack et al. (US Pub 2006/0074788) in view of Shan et al. (US Patent 10,242,019) and in further view of Guerrero et al. (US Patent 11,017,474).
Regarding claim 1, Grizack discloses a method for generating predictive and event-based action recommendations, the method comprising:
receiving, by one or more processors and from at least one data source, input data representative of a user (see abstract; 0072, 0096, 0125);
classifying, by the one or more processors and using a first machine learning model, the input data based on one or more personas representative of user characteristics to generate classified input data, wherein the one or more personas include at least one user persona representative of the user;
identifying, by the one or more processors and from the input data, at least one event associated with the user, wherein the at least one event has an impact on a goal to be achieved by the user (para 0125 and 0127-0132; para 0155; 0114, 0116); and
generating, by the one or more processors and based on the at least one event (see abstract; 0072, 0096, 0125) and the classified input data (para 0080-0085 – such as gender, marital status, ethnicity, occupation, education level), a personalized recommendation for the user, wherein the personalized recommendation comprises a set of actions predicted to achieve the goal based on the impact on the goal caused by the at least one event (see abstract – “providing to the advisee a recommended asset allocation and an indication of the probability that the future financial obligation will be met based on the advisee's current financial situation and the recommended asset allocation”; para 0105, 0160).
Grizack does not disclose classifying, by the one or more processors and using a first machine learning model, the input data based on one or more personas representative of user characteristics to generate classified input data, wherein the one or more personas include at least one user persona representative of the user;
And wherein the personalized recommendation for the user using one or more second machine learning models.
Shan discloses classifying, by the one or more processors and using a first machine learning model, the input data based on one or more personas representative of user characteristics to generate classified input data, wherein the one or more personas include at least one user persona representative of the user (col. 8, lines 10-60; col. 10 lines 28-55; fig. 10);
Therefore, it would have been obvious to a person of ordinary skilled in the art before the effective filing date of the claimed invention to modify Grizack with the teachings of Shan such that the “segmentation provides advantages over other segmentation systems that make use of demographic information to find groups of ‘like’ individuals” (Shan, col. 7, lines 16-26).
Grizack in view of Shan does not disclose wherein the personalized recommendation for the user using one or more second machine learning models.
Guerrero discloses wherein the personalized recommendation for the user using one or more second machine learning models (col. 10, line 29 – col. 11, line 14; col. 2, lines 18-29).
Therefore, it would have been obvious to a person of ordinary skilled in the art before the effective filing date of the claimed invention to modify Grizack in view of Shan with the teachings of Guerrero in order to assist the user in dealing with the life events and upcoming expenses and income using machine learning techniques such that it is faster and more efficient than Monte Carlo simulation (Guerrero, col. 3, lines 35-41).
Regarding claim 2, Guerrero discloses further comprising:
identifying, by the one or more processors, a misalignment between multiple events associated with the user; and remediating, by the one or more processors, the misalignment (col. 3, lines 11-24; col. 8, lines 5-24).
Regarding claim 3, Guerrero discloses wherein identifying the at least one event comprises: predicting, by the one or more processors and using a third machine learning model, the at least one event based on the input data (col. 2, lines 59 – col. 3, lines 10).
Regarding claim 4, Guerrero discloses wherein identifying the at least one event comprises: receiving, by the one or more processors, the at least one event from the user (col. 2, lines 30-38).
Regarding claim 5, Grizack discloses wherein the user characteristics include at least one of a user career or a user salary (para 0108).
Regarding claim 9, Guerrero discloses further comprising:
generating, by the one or more processors, a personalized user recommendation display for the user; and displaying, by the one or more processors, the personalized user recommendation display to the user (col. 8, lines 25-61; col. 9, lines 16-50).
Regarding claim 10, Guerrero discloses wherein generating the personalized user recommendation display is based on one or more user preferences (col. 6, lines 15-36).
Regarding claim 11, see rejection of claim 1.
Regarding claim 12, see rejection of claim 2.
Regarding claim 13, see rejection of claim 3.
Regarding claim 14, see rejection of claim 4.
Regarding claim 15, see rejection of claim 5.
Regarding claim 19, see rejection of claim 9.
Regarding claim 20, see rejection of claim 10.
Claims 7 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Grizack et al. (US Pub 2006/0074788) in view of Shan et al. (US Patent 10,242,019) and in further view of Guerrero et al. (US Patent 11,017,474) and in view of Breitweiser, Edward (US Pub 2023/0267689).
Regarding claim 7, Grizack, Shan, and Guerrero discloses the method of claim 1.
Grizack, Shan, and Guerrero does not disclose wherein the at least one data source includes an extended reality (XR) data source.
Breitweiser discloses wherein the at least one data source includes an extended reality (XR) data source (para 0033-0036, para 0053- “input data, type, write or speak text or content”).
Therefore, it would have been obvious to a person of ordinary skilled in the art before the effective filing date of the claimed invention to modify Grizack, Shan, and Guerrero with the teachings of Breitweiser such that the user be fully immersed in an XR environment (Breitweiser, para 0046).
Regarding claim 17, see rejection of claim 7.
Claims 8 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Grizack et al. (US Pub 2006/0074788) in view of Shan et al. (US Patent 10,242,019) and in further view of Guerrero et al. (US Patent 11,017,474) and in view of Kurani et al. (US Pub 2025/0069049).
Regarding claim 8, Grizack, Shan, and Guerrero discloses the method of claim 1.
Grizack, Shan, and Guerrero does not disclose wherein the one or more second machine learning models includes a generative artificial intelligence using a large language machine learning model.
Kurani discloses wherein the one or more second machine learning models includes a generative artificial intelligence using a large language machine learning model (para 0029).
Therefore, it would have been obvious to a person of ordinary skilled in the art before the effective filing date of the claimed invention to modify Grizack, Shan, and Guerrero with the teachings of Kurani in order to use a LLM to provide recommendations more efficiently.
Regarding claim 18, see rejection of claim 8.
Allowable Subject Matter
Claims 6 and 16 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NAFIZ E HOQUE whose telephone number is (571)270-1811. The examiner can normally be reached M-F 8-5.
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/NAFIZ E HOQUE/ Primary Examiner, Art Unit 2693