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 AIA .
Status of Claims
This communication is a Final Office action in response to communications received on 10/13/2025. Claims 1-20 have been amended. Therefore, claims 1-20 are currently pending and have been addressed below.
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 a judicial exception without a practical application and significantly more.
Step 1: Identifying Statutory Categories
When considering subject matter eligibility under 35 U.S.C. § 101, it must be determined whether the claims are directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter (i.e., Step 1). In the instant case, claims 1-13 are directed to a system (i.e. a machine). Claims 14-19 are directed to a method (i.e. a process). Claim 20 is directed to a non-transitory computer-readable storage medium (i.e. an article of manufacture). Thus, each of these claims fall within one of the four statutory categories. Nevertheless, the claims fall within the judicial exception of an abstract idea.
Step 2A: Prong One: Abstract Ideas
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention recites an abstract idea. Independent claim 1, analogous to independent claims 14 and 20 recite: A system of using models to generate profile-based path displays, the system comprising: information regarding a plurality of paths each associated with a different outcome corresponding to a set of user characteristics and a set of activities, and to construct a user-specific path display based on one or more profiles; receives a set of data that includes characteristics of a user; construct a profile for the user based on the set of data, wherein the profile indicates a time-aware trajectory of skills of the user; construct a path for the user to the profile of the user, the path including a target outcome and one or more associated activities that correspond to the trajectory of the user in accordance with the profile; and generating a path display based on the constructed path, wherein the generated path display includes a set of recommendations regarding the target outcome and the associated activities for the user.
The limitations as drafted, is a process that, under its broadest reasonable interpretation, falls under at least the abstract groupings of:
Certain methods of organizing human activity (commercial or legal interactions (including advertising, marketing or sales activities or behaviors; business relations; (managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions)). As independent claims discuss generating a set of recommendation paths for a user, regarding the target outcome and the associated activities for the user based on the profile of the user, which is one of certain methods of organizing human activity.
Dependent claims 2-13 and 15-19 add additional limitations, for example: (claims 2 and 15), determine a relevancy label for one or more of the activities specified by the path constructed for the user (claim 3) modify the relevancy label based on a physical characteristic specified by the profile of the user; (claim 4) modify the relevancy label based on one or more of an emotional intelligence score and a positive intelligence score specified by the profile of the user; (claims 5 and 16) determine a relevancy label for one or more study areas specified by the path constructed for the user
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profile of the user; (claims 7 and 17) determine a relevancy label for one or more careers specified by the path constructed for the user , and wherein identifying the careers is based on the relevancy label; (claim 8) identify one or more recommended study areas and a study area relevance factor for one or more of the careers the study area relevance factor being indicative of a relative importance of a study area with respect to the one or more careers; and modify the relevancy label for one or more of the careers based on the one or more recommended study areas of the user and the study area relevance factor; (claims 9 and 18) determine a relevancy label for one or more learning institutions specified by the path constructed for the user
Step 2A: Prong Two
This judicial exception is not integrated into a practical application because the claims merely describe how to generally “apply” the abstract idea. In particular, the claims only recite the additional elements – processor, memory, machine learning models, communication interface, network, structured data, user device (claim 1) database (claims 11 and 19) non-transitory computer-readable storage medium (claim 20). These additional elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using generic computer components. Simply implementing the abstract idea on generic computer components is not a practical application of the abstract idea, as it adds the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, as discussed in MPEP 2106.05(f). The limitations generally link the abstract idea to a particular technological environment or field of use (such as computing or machine learning, see MPEP 2106.05(h)). The specification does not describe the computer system in any detail, see specification Figure 19 and para 0142, recites: ”The components contained in the computer system 600 of FIG. 19 are those typically found in computer systems that may be suitable for use with embodiments of the present invention and are intended to represent a broad category of such computer components that are well known in the art. Thus, the computer system 600 of FIG. 19 can be a personal computer, hand held computing device, telephone, mobile computing device, workstation, server, minicomputer, mainframe computer, or any other computing device.” Thus, there can be no dispute that the computer elements recited are not of a particular machine, but rather generic computer elements performing generic computer functions. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements 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 generic computer implementation and do not impose a meaningful limit to integrate the abstract idea into a practical application.
Step 2B:
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to discussion of integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply an exception and generally link the abstract idea to a particular technological environment or field of use. Furthermore, the above-mentioned additional elements do not amount to significantly more than the abstract idea, and fail to include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Thus, nothing in the claim adds significantly more to the abstract idea. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements 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. The claims are ineligible. Therefore, since there are no limitations in the claim that transform the exception into a patent eligible application such that the claim amounts to significantly more than the exception itself, the claims are rejected under 35 USC 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or non-obviousness.
Claims 1, 13, 14 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Varga et al. (US 2020/0302564 A1), hereinafter “Varga”, over Xie et al. (US 2019/0303798 A1), hereinafter “Xie”.
Regarding Claim 1, Varga teaches A system of using models to generate profile-based path displays, the system comprising: memory that stores: information regarding a plurality of paths each associated with a different outcome corresponding to a set of user characteristics and a set of activities, and one or more machine learning models trained to construct a user-specific path display based on one or more profiles; a communication interface that communicates with a user device over a communicates network, wherein the communication interface receives a structured set of data that includes characteristics of a user of the user device; a processor in communication with a memory and including instructions executable by the processor to:(Varga, Abstract; See at least Varga Figure 7 and para 0029, teaches the computing environment including one or more processor(s) and memory; para 0122, non-volatile computer-readable storage media; para 0055, computing environments may include a server computer or any other type of computer system capable of performing one or more tasks or functions associated with creating, modifying, updating, deleting and/or presenting educational or career guidance that can be customized based on the user profiles; Varga, para 0022, identify one or more vocations, educational programs or career paths that may be most interesting to the user based on the defined user profile Varga, para 0002 and para 0088, machine learning techniques to find the meaningful patterns and knowledge in collected data);
construct a profile for the user based on the structured set of data, wherein the profile indicates a ... of skills of the user; construct a path for the user by applying one or more of the machine-learning models to the profile of the user, the path including a target outcome and one or more associated activities that correspond to the trajectory of the user in accordance with the profile; and (Varga, para 0058, the user profile may categorize and/or identify characteristics of the user including characterization of the user based on the user's interests and activity; Varga teaches storing data throughout, see at least para 0088, knowledge base may store a labeled dataset for learning; Varga para 0021, social type (i.e. clubs, hobbies, groups, etc.), travel type and/or places-to-live type (i.e. locations or areas recommended to the user that may offer opportunities for engaging in a particular vocational action, such as education or employment); Varga, para 0058, the user profile may categorize and/or identify characteristics of the user including characterization of the user based on the user's interests and activity).
generating a path display for the user device based on the constructed path, wherein the generated path display includes a set of recommendations regarding the target outcome and the associated activities for the user (Varga, para 0024, apply predictive modeling techniques to rank vocational actions that may be pursued by the user, including career, vocational, educational, volunteer, geographical, and social options for the user based on the predicted likelihood that a recommended career, vocational and/or educational option (referred to herein collectively as “vocational action”) would be found interesting to the user receiving the recommendations; para 0055, recommendations to users based on individual user profiles).
Yet, Varga does not appear to explicitly teach and in the same field of endeavor Xie teaches time-aware trajectory (Xie, Abstract, teaches profile and/or usage data of a social networking service is leveraged to automatically generate potential career paths for users... specific recommendations as to actions the users can take to increase their odds of progressing along particular career paths; Xie teaches progression of time, see at least para 0003, Many careers follow a limited number of potential progressions. For example, a medical doctor almost always will have an undergraduate degree in a scientific field (e.g., Chemistry, Biology, Pre-Med), followed by attendance at an accredited medical school, followed by a residency.... Further, Xie, para 0018, estimate the expected time spent at a particular position and the probability of moving to the next position).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Varga with time-aware trajectory as taught by Xie with the motivation for providing recommendations related to career path (Xie, para 0001). The Varga invention now incorporating the Xie invention, has all the limitations of claim 1.
Regarding Claim 13, Varga, now incorporating Xie, teaches The system of claim 1, wherein the processor executes furtherone or more machine-learning models based on feedback from one or more users (Varga, para 0002, machine learning techniques to find the meaningful patterns and knowledge in collected data; para 0102, Users receiving and reviewing the report generated by the reporting engine may provide user input as feedback which can to improve the recommendations and vocational action presented in subsequent reports. Feedback and comments from the user may be inputted via vocational application user interface; para 0103, feedback and feedback data can be collected, recorded and measured by using recording devices).
Regarding claims 14 and 20, the claims are an obvious variant to claim 1 above, and are therefore rejected on the same premise. Varga further teaches a method comprising: accessing, at a processor in communication with a memory and a non-transitory computer-readable storage medium having instructions. See at least Varga, Figure 7 and para 0029, teaches the computing environment including one or more processor(s) and memory; para 0122 -0127, non-volatile computer-readable storage media and computer readable program instructions.
Claims 2-12 and 15-19 are rejected under 35 U.S.C. 103 as being unpatentable over Varga, Xie, and over Wood et al. (US 2002/0045154 A1), hereinafter “Wood”.
Regarding Claim 2, Varga, now incorporating Xie, teaches The system of claim 1, wherein the processor executes furtherof the activities specified by the path constructed for the userand wherein identifying the activities is further based on the ... label (Varga teaches storing data throughout, see at least para 0088, knowledge base may store a labeled dataset for learning; Varga para 0021, social type (i.e. clubs, hobbies, groups, etc.), travel type and/or places-to-live type (i.e. locations or areas recommended to the user that may offer opportunities for engaging in a particular vocational action, such as education or employment); Varga, para 0058, the user profile may categorize and/or identify characteristics of the user including characterization of the user based on the user's interests and activity).
Yet, Varga and Xie do not appear to explicitly teach and in the same field of endeavor Wood teaches relevancy (Wood, para 0290, Within database all of this content is stored and each element is recorded with a relative relevance strength indicator. A strength indicator value is stored in database... As the system receives feedback from users, reliance values may be increased or decreased to reflect the interest. This allows the system to learn and improve the accuracy of the relevance values over time.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Varga and Xie with relevancy as taught by Wood with the motivation for a relative relevance strength indicator stored in a database, where values may be increased or decreased to reflect the interest of users which allows the system to learn and improve the accuracy of the relevance values over time (Wood, para 0290). The Varga and Xie invention now incorporating the Wood invention, has all the limitations of claim 2.
Regarding Claim 3, Varga, now incorporating Xie and Wood, teaches The system of claim 2, wherein the processor executes further specified by the profile of the user (Varga, para 0088, teaches storing a labeled dataset; para 0055, teaches the computing environments are capable of performing one or more tasks including modifying data. Varga, para 0058, the user profile may categorize and/or identify characteristics of the user including characterization of the user based on the user's interests and activity).
Yet, Varga and Xie do not appear to explicitly teach and in the same field of endeavor Wood teaches relevancy (Wood, para 0290, Within database all of this content is stored and each element is recorded with a relative relevance strength indicator. A strength indicator value is stored in database... As the system receives feedback from users, reliance values may be increased or decreased to reflect the interest. This allows the system to learn and improve the accuracy of the relevance values over time.) physical characteristic (Wood, para 0137, teaches physical health).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Varga and Xie with relevancy … physical characteristic as taught by Wood with the motivation for a relative relevance strength indicator stored in a database, where values may be increased or decreased to reflect the interest of users which allows the system to learn and improve the accuracy of the relevance values over time (Wood, para 0290).
Regarding Claim 4, Varga, now incorporating Xie and Wood, teaches The system of claim 2, wherein the processor executes furtherone or more of an ... specified by the profile of the user (Varga, para 0088, teaches storing a labeled dataset; para 0055, teaches the computing environments are capable of performing one or more tasks including modifying data. Varga, para 0058, the user profile may categorize and/or identify characteristics of the user including characterization of the user based on the user's interests and activity). Yet, Varga and Xie does not appear to explicitly teach and in the same field of endeavor Wood teaches relevancy (Wood, para 0290, Within database all of this content is stored and each element is recorded with a relative relevance strength indicator. A strength indicator value is stored in database... As the system receives feedback from users, reliance values may be increased or decreased to reflect the interest. This allows the system to learn and improve the accuracy of the relevance values over time.) emotional intelligence score and a positive intelligence score (Wood, para 0108 – 0126, teaches a variety of tests to measure personality, creativity and intelligence, including para 0124 teaches emotional intelligence, para 0120-0121, teaches IQ tests and intelligence tests).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Varga and Xie with relevancy … emotional intelligence score and a positive intelligence score as taught by Wood with the motivation for a relative relevance strength indicator stored in a database, where values may be increased or decreased to reflect the interest of users which allows the system to learn and improve the accuracy of the relevance values over time (Wood, para 0290).
Regarding Claim 5, Varga, now incorporating Xie, teaches The system of claim 1, wherein the processor executes furtherspecified by the path constructed for the user and wherein identifying the study areas is based on the ... label (Varga, para 0088, teaches storing a labeled dataset; para 0022, a user profile may be defined, which may include a plurality of user parameter values describing the user and the user data set; para 0021, educational path or career path that might interest the user (referred to herein as “vocational actions”) which may be organized by the type of vocational action being recommended. … areas recommended to the user that may offer opportunities for engaging in a particular vocational action, such as education or employment).
Yet, Varga does not appear to explicitly teach and in the same field of endeavor Wood teaches relevancy (Wood, para 0290, Within database all of this content is stored and each element is recorded with a relative relevance strength indicator. A strength indicator value is stored in database... As the system receives feedback from users, reliance values may be increased or decreased to reflect the interest. This allows the system to learn and improve the accuracy of the relevance values over time.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Varga and Xie with relevancy as taught by Wood with the motivation for a relative relevance strength indicator stored in a database, where values may be increased or decreased to reflect the interest of users which allows the system to learn and improve the accuracy of the relevance values over time (Wood, para 0290). The Varga and Xie invention now incorporating the Wood invention, has all the limitations of claim 5.
Regarding Claim 6, Varga, now incorporating Xie and Wood, teaches The system of claim 5, wherein the processor executes furtherspecified by the profile of the user (Varga, para 0088, teaches storing a labeled dataset; para 0055, teaches the computing environments are capable of performing one or more tasks including modifying data. Varga, para 0068, a user data’s including a high school or college transcript, GED certificates, standardized testing and/or entrance exam scores. The additionally provided educational information can further assist with recommending vocational action to a user. For example, by identifying vocational action that align with the educational strengths of the user based on grades and test scores, as well as presenting appropriate educational institutions that a user would most likely be accepted to attend). Yet, Varga and Xie do not appear to explicitly teach and in the same field of endeavor Wood teaches relevancy (Wood, para 0290, Within database all of this content is stored and each element is recorded with a relative relevance strength indicator. A strength indicator value is stored in database... As the system receives feedback from users, reliance values may be increased or decreased to reflect the interest. This allows the system to learn and improve the accuracy of the relevance values over time.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Varga and Xie with relevancy as taught by Wood with the motivation for a relative relevance strength indicator stored in a database, where values may be increased or decreased to reflect the interest of users which allows the system to learn and improve the accuracy of the relevance values over time (Wood, para 0290).
Regarding Claim 7, Varga, now incorporating Xie, teaches wherein the processor executes furtherspecified by the path constructed for the user, and wherein identifying the careers is based on the ... (Varga, para 0088, teaches storing a labeled dataset; Varga, para 0024, recommended career, vocational option; para 0022, a user profile may be defined, which may include a plurality of user parameter values describing the user and the user data set. Embodiments of the disclosure may further use the defined user profile in conjunction with a knowledge base of historical data to further identify one or more vocations, educational programs or career paths that may be most interesting to the user based on the defined user profile).
Yet, Varga and Xie do not appear to explicitly teach and in the same field of endeavor Wood teaches relevancy (Wood, para 0290, Within database all of this content is stored and each element is recorded with a relative relevance strength indicator. A strength indicator value is stored in database... As the system receives feedback from users, reliance values may be increased or decreased to reflect the interest. This allows the system to learn and improve the accuracy of the relevance values over time.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Varga and Xie with relevancy as taught by Wood with the motivation for a relative relevance strength indicator stored in a database, where values may be increased or decreased to reflect the interest of users which allows the system to learn and improve the accuracy of the relevance values over time (Wood, para 0290). The Varga and Xie invention now incorporating the Wood invention, has all the limitations of claim 7.
Regarding Claim 8, Varga, now incorporating Xie and Wood, teaches The system of claim 7, wherein the processor executes furtheridentify one or more recommended study areas and a study area relevance factor for one or more of the careers, the study area relevance factor being indicative of a relative importance of a study area with respect to the one or more careers; and modify the ... label for one or more of the careers based on the one or more recommended study areas of the user and the study area relevance factor (Varga, para 0096, careers or vocations, which may be ranked; para 0101, FIG. 5b , the provided report can compile course & curriculum data from each educational institution that may be relevant to the selected career or vocation option being viewed by the user. For example, in the drawings of FIG. 5b , a user has selected a career option for “Civil Engineer” and as part of the user's selection of the civil engineer profession, the report includes an expandable section and subsections providing a plurality of options for earning a degree from a civil engineering program; Varga, para 0088, teaches storing a labeled dataset; para 0055, teaches the computing environments are capable of performing one or more tasks including modifying data; para 0024, recommended career, vocational option).
Yet, Varga and Xie do not appear to explicitly teach and in the same field of endeavor Wood teaches relevancy (Wood, para 0290, Within database all of this content is stored and each element is recorded with a relative relevance strength indicator. A strength indicator value is stored in database... As the system receives feedback from users, reliance values may be increased or decreased to reflect the interest. This allows the system to learn and improve the accuracy of the relevance values over time.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Varga and Xie with relevancy as taught by Wood with the motivation for a relative relevance strength indicator stored in a database, where values may be increased or decreased to reflect the interest of users which allows the system to learn and improve the accuracy of the relevance values over time (Wood, para 0290).
Regarding Claim 9, Varga, now incorporating Xie, teaches The system of claim 1, wherein the processor executes furtherspecified by thepath constructed for the user, and wherein identifying the learning institutions is based on the ... label (Varga, para 0088, teaches storing a labeled dataset; para 0022, a user profile may be defined; para 0021, educational path or career path that might interest the user (referred to herein as “vocational actions”) which may be organized by the type of vocational action being recommended. … areas recommended to the user that may offer opportunities for engaging in a particular vocational action, such as education or employment; Figure 5B, teaches one or more learning institutions including Cornell University and Clarkson University).
Yet, Varga and Xie do not appear to explicitly teach and in the same field of endeavor Wood teaches relevancy (Wood, para 0290, Within database all of this content is stored and each element is recorded with a relative relevance strength indicator. A strength indicator value is stored in database... As the system receives feedback from users, reliance values may be increased or decreased to reflect the interest. This allows the system to learn and improve the accuracy of the relevance values over time.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Varga and Xie with relevancy as taught by Wood with the motivation for a relative relevance strength indicator stored in a database, where values may be increased or decreased to reflect the interest of users which allows the system to learn and improve the accuracy of the relevance values over time (Wood, para 0290). The Varga and Xie invention now incorporating the Wood invention, has all the limitations of claim 9.
Regarding Claim 10, Varga, now incorporating Xie and Wood, teaches The system of claim 9, wherein the processor executes furtherone or more preferences indicated by the profile of the user (Varga, para 0088, teaches storing a labeled dataset; para 0022, a user profile may be defined; para 0055, teaches the computing environments are capable of performing one or more tasks including modifying data; Figure 5B, teaches one or more learning institutions including Cornell University and Clarkson University).
Yet, Varga and Xie do not appear to explicitly teach and in the same field of endeavor Wood teaches relevancy (Wood, para 0290, Within database all of this content is stored and each element is recorded with a relative relevance strength indicator. A strength indicator value is stored in database... As the system receives feedback from users, reliance values may be increased or decreased to reflect the interest. This allows the system to learn and improve the accuracy of the relevance values over time.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Varga and Xie with relevancy as taught by Wood with the motivation for a relative relevance strength indicator stored in a database, where values may be increased or decreased to reflect the interest of users which allows the system to learn and improve the accuracy of the relevance values over time (Wood, para 0290).
Regarding Claim 11, Varga, now incorporating Xie, teaches The system of claim 1, wherein the processor executes further displafor the user device, ...wherein constructing the profile of the user is ...presented by the (Varga, para 0088, teaches storing a labeled dataset; para 0022, a user profile may be defined, which may include a plurality of user parameter values describing the user and the user data set; Varga, para 0125, to display data to a user and can be, for example, a computer monitor or screen).
Yet, Varga and Xie do not appear to explicitly teach and in the same field of endeavor Wood teaches retrievand generate a question... the question display presenting a subset of the questions ... based on responses to one or more of the subset of questionquestion display (Wood, para 0363, interface to design a custom page to ask questions; para 0290, Within database all of this content is stored and each element is recorded; Wood, Figures 4-6 and 15, para 0042, a test administration process and system that goes beyond most personality tests .... The system of the present invention dynamically incorporates several personality dimensions, life style, quality of life, cultural context, demographics, and psychographics, as requested by the test administrator or individual user, and controls and standardizes the testing protocol, and retains test data and save their test results in a system database, and use the results to obtain personality-based advice and content).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Varga and Xie with retrieve, a plurality of questions from the database; and generate a question... the question display presenting a subset of the questions ... based on responses to one or more of the subset of question; ... question display as taught by Wood with the motivation for a relative relevance strength indicator stored in a database, where values may be increased or decreased to reflect the interest of users which allows the system to learn and improve the accuracy of the relevance values over time (Wood, para 0290). The Varga and Xie invention now incorporating the Wood invention, has all the limitations of claim 11.
Regarding Claim 12, Varga, now incorporating Xie and Wood, teaches The system of claim 11, wherein theprocessor executes further instructions to: determine one or more personality factors based on ... included in the profile of the user (Varga, para 0019, From the user data set, a plurality of user parameter values can be generated that may describe the characteristics, interests, features, strengths and personality of the user.)
Yet, Varga and Xie do not appear to explicitly teach and in the same field of endeavor Wood teaches the responses the personality factors (Wood, para 0032, asks 70 questions and aggregates the responses; para 0142, these questions measure personality dimensions; For example, what traits one values most in other people. Or what key aspects of a job are necessary to make one happy, etc.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Varga and Xie with the responses the personality factors as taught by Wood with the motivation for a relative relevance strength indicator stored in a database, where values may be increased or decreased to reflect the interest of users which allows the system to learn and improve the accuracy of the relevance values over time (Wood, para 0290).
Regarding Claim 15, the claim recites analogous limitations to claim 2 above, and is therefore rejected on the same premise.
Regarding Claim 16, the claim recites analogous limitations to claim 5 above, and is therefore rejected on the same premise.
Regarding Claim 17, the claim recites analogous limitations to claim 7 above, and is therefore rejected on the same premise.
Regarding Claim 18, the claim recites analogous limitations to claim 9 above, and is therefore rejected on the same premise.
Regarding Claim 19, the claim recites analogous limitations to claim 11 above, and is therefore rejected on the same premise.
Response to Arguments
Applicant’s arguments filed on 10/13/2025 have been fully considered but they are not persuasive.
Regarding 35 U.5.C. § 101 rejections: Examiner has updated the 101 rejections in light of the most recent claim amendments. Applicant’s arguments have been fully considered but are found unpersuasive and Examiner maintains the 101 rejection.
With respect to Applicants remarks that the claims are not directed towards an abstract idea, the Examiner respectfully disagrees, as the claims are directed to at least the abstract grouping of certain methods of organizing human activity as explained in the above 101 analysis. While Applicant argues additional elements (remarks, page 9) “machine learning models” under prong one, Examiner respectfully notes additional elements are considered in Step 2A: Prong Two and Step 2B, not in Prong One.
Further, with respect to Applicant’s remarks on improvements in career path services (remarks page 10), Examiner respectfully does not find the assertion persuasive because Applicant does not explain how or why the limitations of the claims recite specific technical improvements. Applicant's arguments amount to general allegations that the claims define a patent eligible invention without specifically pointing out how the language of the claims reflect a practical application (e.g., how the claims reflect an improvement). Further, with respect to machine learning models, machine learning is recited at such a high level that it amounts to generally linking the abstract idea to the field of machine learning and merely using machine learning as a tool to apply the abstract idea (See MPEP 2106.04(d)(I)). With respect to Applicant’s remarks on Core Wireless, the claims in Core Wireless were directed to an improved user interface for computing devices which comprised an application summary that could be reached directly from a main menu, specified a particular manner in which the summary window must be accessed, a limited set of data which was displayed in the summary window, and that the window was displayed while the one or more applications are in an unlaunched state. Each of these specific limitations disclosed a specific manner of displaying a limited set of information to the user. Here, unlike the limitations of Core Wireless, the instant claimed invention does not represent a technological improvement to information display, as the claimed interface is at a high level of generality which does not purport to bring about some benefit to the use of a computing device. Therefore, the claimed limitations are distinct from those of Core Wireless. Further, Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. Each step does no more than require a generic
computer to perform generic computer functions. The claims do not, for example, purport to improve the functioning of the computer itself. In addition, the claims do not affect an improvement in any other
technology or technical field. The specification spells out different generic equipment and parameters that might be applied using the concept and the particular steps such conventional processing would entail based on the concept of information access. Thus, the claims at issue amount to nothing significantly more than instructions to apply the abstract idea using some unspecified, generic computer(s). Therefore, Applicants remarks are found unpersuasive and Examiner maintains the 101 rejection.
Regarding 35 U.S.C. § 103 rejections. With respect to the prior art rejections, Applicants arguments have been considered but are moot in light of the most recent claim amendments as the Examiner has updated the rejections with the Xie reference.
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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/R.R.N./Examiner, Art Unit 3629 /LYNDA JASMIN/Supervisory Patent Examiner, Art Unit 3629