DETAILED ACTION
The following is a Non-Final, First Office Action on the Merits in response to communications filed May 17, 2024. Claims 1–20 are currently pending.
Claim Objections
Claims 10–11 and 18 are objected to because of the following informalities:
Claims 10 and 18 recite “the trained machine learning model” in the element for “deploying”. Although the claims previously recite an element for “training a machine learning model,” Examiner recommends amending the claims to recite “deploying the
Claim 11 recites “the evaluation output of the second user” in the element for “modifying”. However, claim 11 previously recites “an evaluation output associated with a second user” in the element for “receiving”. In view of the “receiving” element, Examiner recommends amending the claim to recite “modifying … the evaluation output [[of]] associated with the second user” in order to avoid issues of clarity under 35 U.S.C. 112(b).
Appropriate correction is required.
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 6–7, 9–10, 17, and 20 are 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.
Claim 6 recites “wherein the one or more user input objects further comprise at least a first user input object presented to the first user at a first time” and “determining the first time … based at least in part upon the user input from the first user provided via the first user input object.” It is unclear how the first time can be determined based upon inputs provided in response to an object presented at the first time.
Claim 6 further recites “the user input” in lines 4–5. There is insufficient antecedent basis for this limitation in the claim.
For purposes of examination, claim 6 is interpreted as reciting “determining one or more user inputs from the first user provided via the first user input object”.
In view of the above, claim 6 is rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
Claim 7, which depends from claim 6, inherits the deficiencies described above. As a result, claim 7 is similarly rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
Claim 9 recites “wherein determining one or more evaluation attributes … comprises”. However, claim 1 previously recites “determining one or more evaluation attributes”. As a result, the scope of claim 9 is indefinite because it is unclear whether Applicant intends for the recitation of claim 9 to reference the previous recitation of claim 1 or intends to introduce a second, different “one or more evaluation attributes”.
For purposes of examination, claim 9 is interpreted as reciting “wherein determining the one or more evaluation attributes … comprises”.
Further, claims 9, 17, and 20 recite “the comparison” in the element reciting “determining”. There is insufficient antecedent basis for this limitation in the claim.
For purposes of examination, claims 9, 17, and 20 are interpreted as reciting “determining the one or more evaluation attributes associated with the first user based upon comparing the one or more user inputs received from the first user associated with the first user with the plurality of evaluation outputs associated with the plurality of users”.
In view of the above, claims 9, 17, and 20 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
Claim 10 recites “wherein determining one or more evaluation attributes … comprises”. However, claim 1 previously recites “determining one or more evaluation attributes”. As a result, the scope of claim 10 is indefinite because it is unclear whether Applicant intends for the recitation of claim 10 to reference the previous recitation of claim 1 or intends to introduce a second, different “one or more evaluation attributes”.
For purposes of examination, claim 10 is interpreted as reciting “wherein determining the one or more evaluation attributes … comprises”.
In view of the above, claim 10 is rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
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 non-statutory subject matter. Specifically, claims 1–20 are directed to an abstract idea without additional elements amounting to significantly more than the abstract idea.
With respect to Step 2A Prong One of the framework, claim 1 recites an abstract idea. Claim 1 includes elements for “receiving a request for data evaluation associated with a first user”; “generating one or more user input [requests] based upon the request, wherein the one or more user input [requests]are associated with one or more evaluation categories”; “causing presentation of the one or more user input [requests] to the first user”; “receiving one or more user inputs from the first user via the one or more user input [requests]”; “determining one or more evaluation attributes associated with the first user based on the received one or more user inputs”; and “generating an evaluation output indicative of a performance of the first user with respect to at least the one or more evaluation categories.”
The limitations above recite an abstract idea. More particularly, the elements above recite certain methods of organizing human activity for managing personal behavior or relationships or interactions between people because the elements describe a process for evaluating a user performance using a survey. Further, the elements for “determining” and “generating” recite mental processes because the elements embody observations or evaluations that can be practically performed in the human mind or by a human using pen and paper. As a result, claim 1 recites an abstract idea under Step 2A Prong One.
Claims 16 and 19 include substantially similar limitations to those included with respect to claim 1. As a result, claims 16 and 19 recite an abstract idea under Step 2A Prong One for the same reasons as stated above with respect to claim 1.
Claims 2–15, 17–18, and 20 further describe the process for evaluating a user performance using a survey and further recite certain methods of organizing human activity and/or mental processes for the same reasons as stated above. As a result, claims 2–15, 17–18, and 20 recite an abstract idea under Step 2A Prong One.
With respect to Step 2A Prong Two of the framework, claim 1 does not include additional elements that integrate the abstract idea into a practical application. Claim 1 includes additional elements that do not recite an abstract idea under Step 2A Prong One. The additional elements include a computer and a step for generating one or more input objects. When considered in view of the claim as a whole, the additional elements do not integrate the abstract idea into a practical application because the additional computer element is a generic computing component that is merely used as a tool to perform the recited abstract idea, and the remaining additional element does no more than generally link the use of the recited abstract idea to a particular technological environment. As a result, claim 1 does not include any additional elements that integrate the abstract idea into a practical application under Step 2A Prong Two.
As noted above, claims 16 and 19 include substantially similar limitations to those included with respect to claim 1. Although claim 16 further includes a storage device and a processor and claim 19 further includes a storage medium and a processor, the additional elements, when considered in view of the claims as a whole, do not integrate the abstract idea into a practical application because the additional computer elements are generic computing components that are merely used as a tool to perform the recited abstract idea. As a result, claims 16 and 19 do not include any additional elements that integrate the abstract idea into a practical application under Step 2A Prong Two.
Claims 9–10, 17–18, and 20 include additional elements that do not recite an abstract idea under Step 2A Prong One. The additional elements include a step for “accessing a database” (claims 9, 17, and 20) and steps for “training” and “deploying” a machine learning model (claims 10 and 18). When considered in view of the claims as a whole, the additional elements do not integrate the abstract idea into a practical application because the database is a generic computing component that is merely used as a tool to perform the recited abstract idea, and the remaining additional elements do no more than generally link the use of the recited abstract idea to a particular technological environment. As a result, claims 9–10, 17–18, and 20 do not include additional elements that integrate the abstract idea into a practical application under Step 2A Prong Two.
Claims 2–8 and 11–15 do not include any additional elements beyond those included with respect to the claims from which claims 2–8 and 11–15 depend. As a result, claims 2–8 and 11–15 do not include any additional elements that integrate the abstract idea into a practical application under Step 2A Prong Two for the same reasons as stated above.
With respect to Step 2B of the framework, claim 1 does not include additional elements amounting to significantly more than the abstract idea. As noted above, claim 1 includes additional elements that do not recite an abstract idea under Step 2A Prong One. The additional elements include a computer and a step for generating one or more input objects. The additional elements do not amount to significantly more than the recited abstract idea because the additional computer element is a generic computing component that is merely used as a tool to perform the recited abstract idea, and the remaining additional element does no more than generally link the use of the recited abstract idea to a particular technological environment. Further, looking at the additional elements as an ordered combination adds nothing that is not already present when considering the additional elements individually. As a result, claim 1 does not include any additional elements that amount to significantly more than the recited abstract idea under Step 2B.
As noted above, claims 16 and 19 include substantially similar limitations to those included with respect to claim 1. Although claim 16 further includes a storage device and a processor and claim 19 further includes a storage medium and a processor, the additional elements do not amount to significantly more than the recited abstract idea because the additional computer elements are generic computing components that are merely used as a tool to perform the recited abstract idea. Further, looking at the additional elements as an ordered combination adds nothing that is not already present when considering the additional elements individually. As a result, claims 16 and 19 do not include any additional elements that amount to significantly more than the recited abstract idea under Step 2B.
Claims 9–10, 17–18, and 20 include additional elements that do not recite an abstract idea under Step 2A Prong One. The additional elements include a step for “accessing a database” (claims 9, 17, and 20) and steps for “training” and “deploying” a machine learning model (claims 10 and 18). The additional elements do not amount to significantly more than the recited abstract idea because the database is a generic computing component that is merely used as a tool to perform the recited abstract idea, and the remaining additional elements do no more than generally link the use of the recited abstract idea to a particular technological environment. Further, looking at the additional elements as an ordered combination adds nothing that is not already present when considering the additional elements individually. As a result, claims 9–10, 17–18, and 20 do not include additional elements that amount to significantly more than the recited abstract idea under Step 2B.
Claims 2–8 and 11–15 do not include any additional elements beyond those included with respect to the claims from which claims 2–8 and 11–15 depend. As a result, claims 2–8 and 11–15 do not include any additional elements that amount to significantly more than the recited abstract idea under Step 2B for the same reasons as stated above.
Therefore, the claims are directed to an abstract idea without additional elements amounting to significantly more than the abstract idea. Accordingly, claims 1–20 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
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 1–10 and 13–20 are rejected under 35 U.S.C. 103 as being unpatentable over Monasor et al. (U.S. 2019/0188645) in view of Tiwari et al. (U.S. 2024/0330834).
Claims 1, 16, and 19: Monasor discloses a computer-implemented method (See paragraphs 87–88) for data indexing and evaluation in distributed computing environments, the method comprising:
generating one or more user input objects based upon the first user, wherein the one or more user input objects are associated with one or more evaluation categories (See paragraphs 53 and 63, in view of paragraphs 18 and 81, wherein questions are generated based on a comparison between candidate competencies and required competencies, wherein questions are associated with a category of evaluation, and wherein questions are displayed on an applicant interface using input objects);
causing presentation of the one or more user input objects to the first user (See paragraph 18, in view of paragraph 81, wherein questions are displayed on an applicant interface using input objects);
receiving one or more user inputs from the first user via the one or more user input objects (See paragraphs 18–19 and 21, in view of paragraph 81, wherein responses to a current interview question are received in the applicant interface);
determining one or more evaluation attributes associated with the first user based on the received one or more user inputs (See paragraph 21, in view of paragraphs 41–42, wherein competency pairs are determined from applicant responses; see also paragraphs 52–53); and
generating an evaluation output indicative of a performance of the first user with respect to at least the one or more evaluation categories (See paragraphs 18–19, in view of paragraphs 41–42 and 52–53, wherein global interview data and results analysis are presented to an administrator). Monasor does not expressly disclose the remaining claim elements.
Tiwari discloses receiving a request for data evaluation associated with a first user (See paragraph 66, wherein a candidate is requested to work through a series of case studies, questionnaires, and live simulations targeting the required skills).
Monasor discloses a system directed to generating adaptive questionnaires to evaluate job candidate experience. Tiwari discloses a system directed to generating skill development recommendations based on candidate evaluations. Each reference discloses a system directed to evaluating candidates. The technique of requesting an evaluation is applicable to the system of Monasor as they each share characteristics and capabilities; namely, they are directed to evaluating candidates.
One of ordinary skill in the art would have recognized that applying the known technique of Tiwari would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Tiwari to the teachings of Monasor would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate candidate evaluations into similar systems. Further, applying evaluation requests to Monasor would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow improved management.
With respect to claim 16, Monasor discloses a non-transitory storage device; and a processor coupled to the non-transitory storage device, wherein the processor is configured to perform operations (See paragraphs 87–88).
With respect to claim 19, Monasor discloses a computer program product comprising at least one non-transitory computer-readable storage medium having computer program code thereon that, in execution with at least one processor, configures the computer program product for performing operations (See paragraphs 87–88).
Claim 2: Monasor discloses the computer-implemented method according to Claim 1, wherein the request for data evaluation further comprises one or more first user characteristics of the first user, and wherein generating the one or more user input objects is further based upon the one or more first user characteristics (See paragraph 15, in view of paragraph 81, wherein questions are presented based on experience attributes of the applicant; see also paragraphs 51–53).
Claim 3: Monasor discloses the computer-implemented method according to Claim 2, wherein the one or more evaluation categories are selected at least partially based upon the one or more first user characteristics (See paragraph 15, in view of paragraphs 51–53, wherein questions are presented based on experience attributes of the applicant, and wherein questions are associated with competency categories; see also paragraph 81).
Claim 4: Monasor discloses the computer-implemented method according to Claim 1, further comprising determining one or more presentation parameters that define a configuration by which the user input objects are presented to the first user (See FIG. 6A and paragraphs 27 and 51–53, in view of paragraph 81, wherein the customized questionnaire is generated using branching parameters that define an order of questions; see also paragraphs 17 and 21).
Claim 5: Monasor discloses the computer-implemented method according to Claim 4, wherein the one or more presentation parameters comprise a presentation order defining an order in which the one or more user input objects are presented to the user (See FIG. 6A and paragraphs 27 and 51–53, in view of paragraph 81, wherein the customized questionnaire is generated using branching parameters that define an order of questions; see also paragraphs 17 and 21).
Claim 6: Monasor discloses the computer-implemented method according to Claim 1, wherein the one or more user input objects further comprise at least a first user input object presented to the first user at a first time and a second user input object presented to the first user at a second time (See FIG. 6A and paragraphs 27 and 51–53, in view of paragraph 81, wherein the customized questionnaire is generated using branching parameters that define an order of questions; see also paragraphs 17 and 21). Monasor does not disclose the remaining claim elements.
Tiwari discloses determining the first time and the second time based at least in part upon the user input from the first user provided via the first user input (See paragraph 66, wherein recurring evaluations require requesting secondary inputs after a first period of time).
One of ordinary skill in the art would have recognized that applying the known technique of Tiwari would have yielded predictable results and resulted in an improved system for the same reasons as stated above with respect to claim 1.
Claim 7: Monasor discloses the computer-implemented method according to Claim 6, wherein each of the first user input object and the second user input object is associated with a first evaluation category (See paragraph 15 and 56, in view of paragraphs 51–53, wherein multiple questions pertaining to a same competency are presented to the applicant, wherein questions are associated with competency categories; see also paragraph 81).
Claim 8: Monasor discloses the computer-implemented method according to Claim 1, wherein the one or more user input objects further comprise at least: a first user input object associated with a first evaluation category; and a second user input object associated with a second evaluation category (See FIG. 6A and paragraphs 51–53, wherein the question path branches to introduce different competency categories; see also paragraph 81).
Claims 9, 17, and 20: Monasor discloses the computer-implemented method according to Claim 1, wherein determining one or more evaluation attributes associated with the first user with respect to the one or more evaluation categories further comprises:
accessing a database storing a plurality of evaluation outputs generated based upon one or more evaluation attributes associated with a plurality of users (See paragraphs 18–19, wherein global information and analysis results are presented to an administrative user in the context of a database system). Monasor does not disclose the remaining claim elements.
Tiwari discloses comparing the one or more user inputs received from the first user associated with the first user with the plurality of evaluation outputs associated with the plurality of users (See paragraph 26, in view of paragraph 62, wherein real-time information from a given user is utilized to optimize personnel distribution, and wherein real-time information from a given user is further utilized with respect to a machine learning model trained on outputs associated with a plurality of users; see also paragraphs 64–66); and
determining the one or more evaluation attributes associated with the first user based upon the comparison (See paragraph 62, in view of paragraph 26, wherein real-time information from a given user is utilized with respect to a machine learning model trained on outputs associated with a plurality of users to identify skills and proficiencies for the given user; see also paragraphs 64–66).
One of ordinary skill in the art would have recognized that applying the known technique of Tiwari would have yielded predictable results and resulted in an improved system for the same reasons as stated above with respect to claim 1.
Claims 10 and 18: Although Monasor discloses determining one or more evaluation attributes associated with the first user with respect to the one or more evaluation categories (See citations above), Monasor does not disclose the remaining elements of claim 10.
Tiwari discloses training a machine learning model on a plurality of evaluation outputs generated based upon one or more evaluation attributes associated with a plurality of users (See paragraph 62, wherein the machine learning model is trained based on previous predictions); and
deploying the trained machine learning model on the one or more user inputs from the first user to generate the one or more evaluation attributes of the first user (See paragraph 62, wherein the machine learning model is utilized with respect to real-time data).
One of ordinary skill in the art would have recognized that applying the known technique of Tiwari would have yielded predictable results and resulted in an improved system for the same reasons as stated above with respect to claim 1.
Claim 13: Monasor does not disclose the elements of claim 13.
Tiwari discloses determining one or more developmental resources for the first user associated with the one or more evaluation categories, wherein the one or more developmental resources are configured to improve the performance of the first user with respect to the one or more evaluation categories (See paragraphs 65–66, wherein a training path and training resources are recommended to the user with respect to a specific domain); and
providing access for the first user to the one or more developmental resources (See paragraphs 65–66, wherein a training path and training resources are provided to the user with respect to a specific domain).
One of ordinary skill in the art would have recognized that applying the known technique of Tiwari would have yielded predictable results and resulted in an improved system for the same reasons as stated above with respect to claim 1.
Claim 14: Monasor does not disclose the elements of claim 14.
Tiwari discloses identifying an administrative user associated with the first user (See paragraph 67, wherein assessment information is communicated to a manager of the candidate; see also paragraph 26); and
causing transmission of a user notification to the administrative user indicative of the one or more developmental resources determined for the first user (See paragraph 67, wherein assessment information is communicated to a manager of the candidate; see also paragraph 26).
One of ordinary skill in the art would have recognized that applying the known technique of Tiwari would have yielded predictable results and resulted in an improved system for the same reasons as stated above with respect to claim 1.
Claim 15: Monasor does not disclose the elements of claim 15.
Tiwari discloses generating a predictive evaluation output for the first user indicative of a predicted performance of the first user with respect to at least one of the one or more evaluation categories following completion of the one or more developmental resources (See paragraphs 55 and 59, wherein the system predicts improvements in proficiency based on up-skilling program participation).
One of ordinary skill in the art would have recognized that applying the known technique of Tiwari would have yielded predictable results and resulted in an improved system for the same reasons as stated above with respect to claim 1.
Claims 11–12 are rejected under 35 U.S.C. 103 as being unpatentable over Monasor et al. (U.S. 2019/0188645) in view of Tiwari et al. (U.S. 2024/0330834), and in further view of Vesely et al. (U.S. 2013/0211883).
Claim 11: As detailed above, Monasor and Tiwari disclose the elements of independent claim 1. Although Monasor discloses wherein the evaluation output of the first user is generated at a first time (See paragraphs 18–19, wherein analysis reports are generated, and wherein an output is necessarily generated at a given time) and Tiwari discloses modifying evaluation outputs (See paragraph 69, wherein evaluation outputs are modified in view of competency trends), Monasor and Tiwari do not expressly disclose the remaining elements of claim 11.
Vesely discloses receiving an evaluation output associated with a second user at a second time that is later in time than the first time (See paragraph 78, in view of paragraph 85, wherein evaluation outputs for a given user are based on a combination of evaluation outputs provided by other users, and wherein evaluation scores are updated continuously); and
modifying the evaluation output of the first user in response to the evaluation output of the second user (See paragraph 78, in view of paragraph 85, wherein evaluation outputs for a given user are based on a combination of evaluation outputs provided by other users, and wherein evaluation scores are updated continuously).
As disclosed above, Monasor discloses a system directed to generating adaptive questionnaires to evaluate job candidate experience, and Tiwari discloses a system directed to generating skill development recommendations based on candidate evaluations. Vesely discloses a system directed to evaluating members of a professional community. Each reference discloses a system directed to evaluating professionals. The technique of collectively modifying evaluations is applicable to the systems of Monasor and Tiwari as they each share characteristics and capabilities; namely, they are directed to evaluating professionals.
One of ordinary skill in the art would have recognized that applying the known technique of Vesely would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Vesely to the teachings of Monasor and Tiwari would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate professional evaluations into similar systems. Further, applying collective evaluations to Monasor and Tiwari would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow more detailed analysis and more reliable results.
Claim 12: Monasor and Tiwari do not disclose the elements of claim 12.
Vesely discloses wherein the evaluation output of the first user is iteratively updated in response to iterative generation of evaluation outputs associated with a plurality of users other than the first user (See paragraph 78, in view of paragraph 85, wherein evaluation outputs for a given user are based on a combination of evaluation outputs provided by other users, and wherein evaluation scores are updated periodically/continuously).
One of ordinary skill in the art would have recognized that applying the known technique of Vesely would have yielded predictable results and resulted in an improved system for the same reasons as stated above with respect to claim 11.
Conclusion
The following prior art is made of record and not relied upon but is considered pertinent to applicant's disclosure:
Sergott et al. (U.S. 20190318317) discloses a system directed to evaluating job candidates using adaptive surveys.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WILLIAM S BROCKINGTON III whose telephone number is (571)270-3400. The examiner can normally be reached M-F, 8am-5pm, EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Rutao Wu can be reached at 571-272-6045. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/WILLIAM S BROCKINGTON III/ Primary Examiner, Art Unit 3623
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