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 .
Status of Claims
Claims 1-19 were previously pending and subject to a non-final rejection dated October 31, 2025. In Response, submitted April 29, 2056, claims 1, 10, 18, and 19 were amended. Therefore, claims 1-19 are currently pending and subject to the following final rejection.
Response to Arguments
Applicant’s remarks on Page 11 of the Response regarding the previous objection of the claims have been fully considered and are found to be persuasive in view of the amended claims, and these objections are withdrawn.
Applicant’s remarks on Pages 11-13 of the Response, regarding the previous rejection of the claims under 35 U.S.C. 101, have been fully considered and are not found persuasive.
On Pages 11-12 of the Response, Applicant argues “Applicant respectfully submits that amended claim 1 is not directed to an abstract idea. Rather, claim 1 recites a specific computer-implemented processing sequence for transforming source documents into vector representations, generating worker-specific vector sets from those vector representations, generating labeled worker datasets that include both position labels and attribute labels, clustering the labeled worker datasets based on the position and attribute labels, determining an attribute vector set for a given position from worker vector sets of a position cluster associated with the given position, and then using that position-specific attribute vector set in candidate qualification analysis. Claim 1 therefore does not merely recite evaluating candidates or making hiring decisions at a high level. Instead, claim 1 recites a defined sequence for preparing, structuring, reducing, and processing data used in a computerized qualification process.”
Examiner notes, as discussed further in the detailed rejection below, the “processing sequence[s] for transforming source documents into vector representations, generating worker-specific vector sets from those vector representations, generating labeled worker datasets that include both position labels and attribute labels, clustering the labeled worker datasets based on the position and attribute labels, determining an attribute vector set for a given position from worker vector sets of a position cluster associated with the given position, and then using that position-specific attribute vector set in candidate qualification analysis” are the abstract idea processes used to provide the abstract results of “evaluating candidates or making hiring decisions”. While claim 1 is completely devoid of additional elements, independent claims 10 and 19 recite the additional elements of a workforce management system, a processor, and a non-transitory computer readable medium comprising program instructions stored thereon. The presence of these additional elements does not preclude these claims from accurately being determined to recite abstract ideas such as “defined sequence[s] for preparing, structuring, reducing, and processing data used in a … qualification process”, their presence simply indicates that analysis must continue to determine if they integrate the recited abstract idea into a practical application or amount to “significantly more”. In the instant case, these additional elements are recited generically throughout the specification, such that they support the Examiner’s determination that they amount to merely being used as generic tools to perform the recited abstract idea, and therefore fail to integrate the abstract idea into a practical application at Step 2A Prong Two, or to amount to significantly more at Step 2B.
On Page 12 of the Response, Applicant argues “Claim 1 also integrates any alleged judicial exception into a practical application. In particular, claim 1 does not compare a candidate against a generic or undifferentiated body of worker information. Instead, claim 1 first generates labeled worker datasets, then clusters those datasets based on position and attribute labels, wherein each position cluster comprises labeled worker datasets having a position label corresponding to the position and an attribute label that satisfies criteria for the attribute, and then determines an attribute vector set for a given position from worker vector sets of a position cluster associated with the given position. By requiring the use of this clustered and criterion-constrained subset of worker data to generate the position- specific attribute vector set, claim 1 narrows the data carried forward into the comparison stage, reduces the amount of irrelevant data used in the computerized qualification analysis, and improves the efficiency of the overall process. Claim 1 thus recites a specific implementation that improves how a computer system organizes and processes document-derived vector data in order to automate qualification analysis. The specification is consistent with this claimed technical sequence. The application describes obtaining worker data, vectorizing documents, generating worker datasets, clustering worker datasets, extracting worker-cluster attributes, identifying position attributes, vectorizing candidate data, and performing position-candidate vector matching. The application further depicts this staged workflow in, for example, Figures 2 and 5. Amended claim 1 follows that disclosed sequence and uses intermediate labeled-and-clustered data structures to generate a context-relevant attribute vector set for downstream comparison. Thus, claim 1 is not directed merely to certain methods of organizing human activity or to mathematical concepts in the abstract. Rather, claim 1 recites a specific computer-implemented sequence that applies vectorization, labeling, clustering, and position-specific vector generation in a defined manner to improve the efficiency and operation of the automated qualification process. Claim 1 therefore is integrated into a practical application and is patent-eligible under 35 U.S.C. § 101.”
Examiner notes, it appears Applicant is arguing an improvement of abstract businesses process related to the potential issues of “compare a candidate against a generic or undifferentiated body of worker information”; but does not argue any technical improvements (e.g., to the technology of the workforce management system, the processor, or the non-transitory computer readable medium comprising program instructions stored thereon). The Applicant appears to argue the claimed invention provides an abstract business process solution of “narrow[ing] the data carried forward into the comparison stage” which provides additional abstract benefits such as “reduc[ing] the amount of irrelevant data used in the … qualification analysis, and improv[ing] the efficiency of the overall process”. This solution is found in alleged improvements to the abstract ideas of “organiz[ing] and process[ing] document-derived vector data” by performing the abstract ideas of “generat[ing] labeled worker datasets, then cluster[ing] those datasets based on position and attribute labels, wherein each position cluster comprises labeled worker datasets having a position label corresponding to the position and an attribute label that satisfies criteria for the attribute, and then determin[ing] an attribute vector set for a given position from worker vector sets of a position cluster associated with the given position”. As discussed above, the “automated” and “computerized” aspects of the claims amount merely applying a workforce management system (disclosed generically as “a computer system” [specification, para. 25] containing generic components [specification, para. 116]), a processor (disclosed generically as “a computer processor” [specification, para. 116]), and a non-transitory computer readable medium comprising program instructions stored thereon (disclosed at face value as part of the memory [specification, para. 116]) as generic tools to perform the recited abstract idea. Further, no support is found that any of these additional elements or any other technology is improved, only the abstract processes these elements are used to carry out. As noted in MPEP 2106.05(a)(II), an improvement to the abstract idea is not an improvement to the technology.
Examiner also notes, similarly, as discussed above and in the detailed analysis below, “obtaining worker data, vectorizing documents, generating worker datasets, clustering worker datasets, extracting worker-cluster attributes, identifying position attributes, vectorizing candidate data, and performing position-candidate vector matching”, “sequenc[ing] and us[ing] intermediate labeled-and-clustered data structures to generate a context-relevant attribute vector set for downstream comparison”, and “appl[ying] vectorization, labeling, clustering, and position-specific vector generation in a defined manner to improve the efficiency and operation of the … qualification process” are abstract ideas an unhelpful in bringing the claims to eligibility. For the same reasons as discussed above, the inclusion of the descriptor “automated” within the context of this argument fails to demonstrate any integration of these abstract ideas into a practical application, or anything amounting to “significantly more”.
On Pages 12-13 of the Response, Applicant argues “Even if claim 1 were deemed to recite a judicial exception, the ordered combination of claim elements amounts to significantly more. Claim 1 requires a particular arrangement in which document vectorization, worker vector-set generation, generation of labeled worker datasets including position labels and attribute labels, clustering based on those labels using an attribute- label criterion, and determination of a position-specific attribute vector set are performed in sequence before candidate comparison. This is not a generic instruction to apply an abstract idea on a computer. Rather, it is a specific and assertedly non-conventional processing architecture for reducing and structuring document-derived data used in automated qualification determinations. Indeed, the Office Action itself acknowledges that the cited prior art does not teach determining an attribute vector set for a given position based on worker vector sets of an associated position cluster. Accordingly, Applicant respectfully submits that independent claims 1, 10, and 19, as amended, as well as claims depending therefrom, are directed to statutory subject matter under 35 U.S.C. § 101.”
Examiner notes, “requir[ing] a particular arrangement in which document vectorization, worker vector-set generation, generation of labeled worker datasets including position labels and attribute labels, clustering based on those labels using an attribute- label criterion, and determination of a position-specific attribute vector set are performed in sequence before candidate comparison” are abstract ideas describing the abstract ideas of the claimed invention. While these abstract processes may act to filter out unnecessary data in the subsequent comparison process, this abstract filtering in no way changes or improves the technology of the processor, non-transitory computer readable medium, or the computer system acting as the workforce management system. Simply processing less data in one process (i.e. reducing and structuring document-derived data”) does not mean that these technologies themselves are improved, the technology itself remains unchanged.
Examiner further notes, that these processes being “assertedly non-conventional” is moot due to the rejection being found on the grounds of “apply it” and not “well understood, routine, and conventional”, but also because the alleged “non-conventional processing architecture” refers wholly to abstract ideas rather than any additional elements or technical aspects. Additionally, “ ‘“novelty” of any element or steps in a process, or even of the process itself, is of no relevance in determining whether the subject matter of a claim falls within the § 101 categories of possibly patentable subject matter.’ Intellectual Ventures I v. Symantec Corp., 838 F.3d 1307, 1315, 120 USPQ2d 1353, 1358 (Fed. Cir. 2016) (quoting Diamond v. Diehr, 450 U.S. at 188–89, 209 USPQ at 9). See also Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1151, 120 USPQ2d 1473, 1483 (Fed. Cir. 2016)” (MPEP 2106.05(I)).
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 1-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Claims 1-9 are directed to a method (i.e., a process); claims 10-18 are directed to a system (i.e., a machine); claims 19 are directed to a non-transitory computer-readable storage medium (i.e., a machine). Therefore, claims 1-19 all fall within the one of the four statutory categories of invention.
Step 2A, Prong One
Independent claims 1, 10, and 19 substantially recite obtaining documents associated with workers;
vectorizing the documents to generate vector representations of the documents, the vectorizing comprising, for each of the documents obtained, generating a vector representation of the document;
generating, based on the vector representations of the documents, worker vector sets, the generating of the worker vector sets comprising, for each of the workers:
identifying documents associated with the worker; and
generating a worker vector set based on the vector representations of the documents identified as associated with the worker;
generating, based on the worker vector sets, labeled worker datasets comprising position labels and attribute labels, the generation of the labeled worker datasets comprising, for each of the workers:
determining a position of the worker;
determining an attribute of the worker; and
generating a labeled worker dataset comprising:
the vector set for the worker; and
a position label corresponding to the position of the worker determined; and
an attribute label corresponding to the attribute of the worker determined;
clustering, based on the position and attribute labels, the labeled worker datasets to determine position clusters, each of the position clusters associated with a position and comprising a set of one or more labeled worker datasets comprising a position label that corresponds to the position and an attribute label that satisfies criteria for the attribute;
determining, based on the vector sets of the labeled worker datasets, an attribute vector set for a given position, the attribute vector set for the given position determined based on the worker vectors sets of a position cluster of the position clusters that is associated with the given position;
obtaining candidate documents associated with a candidate worker;
vectorizing the candidate documents to generate vector representations of the candidate documents, the vectorizing comprising, for each of the candidate documents, generating a vector representation of the candidate document;
generating, based on the vector representations of the candidate documents, a candidate worker vector set;
comparing the candidate worker vector set to the attribute vector set for the given position to determine whether the candidate worker associated with the candidate worker vector set is qualified for the given position; and
extending, in response to determining that the candidate worker is qualified for the given position, an offer for the given position to the candidate worker.
The limitations stated above are processes/functions that under broadest reasonable interpretation covers “certain methods of organizing human activity” (commercial interactions) of “assessing and implementing workforce management”. (See Specification Para. 1). Therefore, the claims recites an abstract idea.
Step 2A, Prong Two
The judicial exception is not integrated into a practical application. No additional elements were included in independent claim 1. Claims 10 and 19 as a whole amount to: (i) merely invoking generic components as a tool to perform the abstract idea or “apply it” (or an equivalent). The claims recites the additional elements of: (i) a workforce management system (claims 10, 19), (ii) a processor (claims 10, 19), and (iii) non-transitory computer readable medium comprising program instructions stored thereon (claims 10, 19).
The additional elements of (i) a workforce management system, (ii) a processor, and (iii) non-transitory computer readable medium comprising program instructions stored thereon are recited at a high level of generality (see [0025] of the Applicant’s Specification discussing the workforce management system, [0116] discussing the processor, and the non-transitory computer readable medium comprising program instructions stored thereon) such that, when viewed as whole/ordered combination, it amounts to no more than mere instruction to apply the judicial exception using generic computer components or “apply it” (See MPEP 2106.05(f)).
Accordingly, these additional elements, when viewed as a whole/ordered combination [See Figure 6 showing all the additional elements of (i) a workforce management system, (ii) a processor, (iii) non-transitory computer readable medium comprising program instructions stored thereon 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. Thus, the claim is directed to an abstract idea.
Step 2B
As discussed above with respect to Step 2A Prong Two, the additional elements amount to no more than: (i) “apply it” (or an equivalent), and are not a practical application of the abstract idea. The same analysis applies here in Step 2B, i.e., (i) merely invoking the generic components as a tool to perform the abstract idea or “apply it” (See MPEP 2106.05(f)), does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B. Thus, even when viewed as a whole/ordered combination, nothing in the claims adds significantly more (i.e., an inventive concept) to the abstract idea. Thus, the claims 1, 10, and 19 are ineligible.
Dependent Claims 5-9 and 11-18 merely narrow the previously recited abstract idea limitations. For reasons described above with respect to claims 1 and 10 these judicial exceptions are not meaningfully integrated into a practical application or significantly more than the abstract idea. Thus, claims 5-9 and 11-18 are also ineligible.
Novel and Non-Obvious Over the Prior Art
Claims 1-19 are novel and non-obvious over the prior art; however, these claims are subject to the above rejections.
The closest prior art is U.S. Patent Application No. 2018/0232700 to Li et al (hereafter Li). Li discloses efficient recommendation services including job matching services.
The next closest prior art is U.S. Patent Application No. 2022/0180323 to Di Sipio et al (hereafter Di Sipio). Di Sipio discloses generating job recommendations for one or more candidates.
The next closest prior art is U.S. Patent Application No. 2021/0256644 to Cahalane et al (hereafter Cahalane). Cahalane discloses vectorizing career/skill representations for users.
The next closest prior art is U.S. Patent No. 11,803,815 to Agarwal et al (hereafter Agarwal). Agarwal discloses vectorizing career/skill representations of job candidates including attribute values.
While the closest prior art above teaches the various aspects of the claimed invention individually, the combination of these references are not obvious in such a way that they would have been obvious to one of ordinary skill in the art at the time of invention. Specifically, Li in view of Di Sipio and further in view of Cahalane and even further in view of Agarwal does not explicitly disclose “determining, based on the vector sets of the labeled worker datasets, an attribute vector set for a given position, the attribute vector set for the given position determined based on the worker vectors sets of a position cluster of the position clusters that is associated with the given position” in combination with the other recited claims. Therefore, the claims are rendered novel and non-obvious over the prior art.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DAVID G GODBOLD whose telephone number is (571)272-5036. The examiner can normally be reached M-F 8-5.
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/DAVID G. GODBOLD/Examiner, Art Unit 3628
/RUPANGINI SINGH/Primary Examiner, Art Unit 3628
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