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 the Claims
Claims 1-20 were previously pending. Claim 13 was amended in the reply filed January 2, 2026. Claims 1-20 are currently pending.
Response to Arguments
Applicant's arguments filed with respect to the rejection made under § 101 have been fully considered but they are not persuasive. Applicant argues that the claims do not recite an abstract idea. Applicant correctly notes that the claims do not recite travel behaviors (Remarks, 9) and this was the result of a typographical error. However, the same sentence sets forth that the claims recite employment candidate evaluation and Applicant does not explain why this does not fall into the subcategory of certain methods of organizing human activities. The arguments that the claims do not recite an abstract idea because they recite machine learning models (Remarks, 9) does not address the basis of the rejection. The rejection was not premised on a finding that the machine learning models are abstract. They were addressed as additional elements. Their presence in the claim does not mean that an abstract idea is not also recited at this point in the analysis.
"The claims relate to systems and methods for processing documents using machine learning models to generate skill assessments." Remarks, 10. Evan as characterized by Applicant here, aside from the generic machine learning models this describes organizing human activities. See Content Extraction and Transmission. v. Wells Fargo Bank, 776 F.3d 1343 (Fed. Cir. 2014) (recognizing and storing structured data from documents held to be ineligible). "The Examiner has failed to identify a specific limitation(s) that recites an abstract idea." Remarks, 10. This was performed at ¶ 4 of the Non-Final Rejection. "Grouping all of the claim elements together and drawing a general conclusion does not fulfill the examination requirements of the Step 2A analysis." Remarks, 10. This is a mischaracterization of the rejection, which separately identifies the abstract idea and the additional elements and then analyzes them together in accordance with MPEP 2106.
Applicant also argues that the claims integrate the abstract idea into a practical application. "For instance, independent claim 1 recites various elements that cannot properly be characterized as part of any 'abstract idea' such as the machine learning features and recognizing of steps using computer technology. These limitations are significant claim elements that cannot be performed through human activity and thus cannot be interpreted as 'organizing human activity.' Moreover, these technical steps are not commercial or legal interactions or any of the other items that the Office has alleged and cannot be disregarded as part of such interactions at this stage of the eligibility analysis." Remarks, 11. This appears to be another argument that the claims do not recite an abstract idea but it is contained under the heading "Step 2A, Prong Two." It is not persuasive for the same reasons as above.
"Applicants respectfully submit that these additional elements impose meaningful limitations on how one might generate a skill assessment by reciting particular machine learning steps and multiple steps or elements using machine learning models to thereby confine the systems and methods to specific implementation involving specific technical steps." Remarks, 11. The only additional element identified are the machine learning models. The claims merely recite machine learning at a high level in order to evaluate the skills of people. "[P]atents that do no more than claim the application of generic machine learning to new data environments, without disclosing improvements to the machine learning models to be applied, are patent ineligible under § 101." Recentive Analytics, Inc. v. Fox. Corp., Fed Cir. No. 2023-2437 (Apr. 18, 2025) (slip op. at 18).
"Applicants submit that these details represent a specific implementation and do not preempt or monopolize an abstract idea." Remarks, 11. Preemption concerns are resolved by the two-part Alice/Mayo framework and preemption is not a separate test. "[Q]uestions on preemption are inherent in and resolved by the § 101 analysis.... While preemption may signal patent ineligible subject matter, the absence of complete preemption does not demonstrate patent eligibility." Ariosa Diagnostics, Inc. v. Sequenom, Inc., 788 F.3d 1371, 1379 (Fed. Cir. 2015). Cf. OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1362-1363 (Fed. Cir.) (cert. denied, 136 S. Ct. 701, 193 L. Ed. 2d 522 (2015)) ("[T]hat the claims do not preempt all price optimization or may be limited to price optimization in the e-commerce setting do not make them any less abstract.").
"Here, the claims are similar to those of Finjan in that they recite specific steps that accomplish a desired result." Remarks, 12. Applicant does not explain how the claims are similar to Finjan. "Specific steps that accomplish a desired result" also describes the claims in Alice Corp.
"Applicants further note that the claims recite a specific technical solution to technical problems such as reducing false positives to ensure that skill assessments are accurate and viable when created using text documents and character recognition technologies to automate the process using resumes or other documents that contain text suitable for processing and transformation using the claimed invention." Remarks, 12. This describes using generic computer tools (i.e., ubiquitous OCR technology) in order to improve the abstract idea of skill evaluation of people. As in Content Extraction above, recognizing data in documents using computers as tools is not eligible.
Applicant also argues that the claims recite "significantly more" and highlights that there are no prior art rejections. Remarks, 13. However, this is not the test for eligibility. "Even newly discovered judicial exceptions are still exceptions, despite their novelty." July 2015 Update: Subject Matter Eligibility, pg. 3 (noting the novel but ineligible abstract claims in, e.g., Parker v. Flook, 437 U.S. 584 (1978)). See also Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1151, 120 USPQ2d 1473, 1483 (Fed. Cir. 2016) ("a claim for a new abstract idea is still an abstract idea. The search for a § 101 inventive concept is thus distinct from demonstrating § 102 novelty."). See also MPEP 2106.05(I).
"Here, Applicants have been provided with no factual support for the conclusion that any of the specific features of the independent claims were well-known, routine, and conventional at the time of Applicants' invention." Remarks, 13. Applicant addresses neither the finding that the machine learning models are generic and can be used in the same manner across many different environments (See Recentive Analytics above) nor the finding that at the high level claimed the disclosure does not support any significant technical detail as to the model operations themselves (i.e., their middle layers rather than inputs and outputs). Accordingly, the rejection is maintained.
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 (abstract idea without significantly more). Claims are eligible for patent protection under § 101 if they are in one of the four statutory categories and not directed to a judicial exception to patentability. Alice Corp. v. CLS Bank Int'l, 573 U.S. 208 (2014). Claims 1-20, each considered as a whole and as an ordered combination, are directed to a judicial exception (i.e., an abstract idea) without significantly more.
MPEP 2106 Step 2A – Prong 1:
The claims recite an abstract idea reflected in the representative functions of the independent claims—including:
identifying a plurality of text segments from a document;
recognizing a plurality of named entities (NEs) from the plurality of text segments, each NE of the plurality of NEs being tagged with a category in a skill name class or a skill level class;
forming a group of pairs of NEs from the plurality of NEs,
each pair of NEs of the group of pairs of NEs being in the same text segment of the plurality of text segments;
generating an encoding for a specific pair of NEs of the group of pairs of NEs;
classifying the group of pairs of NEs to one or more sets respectively corresponding to one or more skill names;
determining, from a set of encodings for a set of pairs of NEs corresponding to a skill name of the one or more skill names, a skill level,
each pair of NEs of the set of pairs of NEs being respectively tagged with a category in the skill name class and a category in the skill level class;
generating a skill assessment associating the one or more skill names respectively to one or more skill levels based on the determining.
These limitations taken together qualify as a certain method of organizing human activities because they recite collecting, analyzing, and outputting information for employment candidate evaluation based on their skills (i.e., in the terminology of the 2019 Revised Guidance, fundamental economic practices; managing personal behavior or relationships or interactions between people (including social activities and following rules or instructions)). Additionally, aside from the general technological environment (addressed below), it covers purely mental processes (e.g., a person observing skills from a document, evaluating them, and arriving at a judgment on a skill assessment).
It shares similarities with other abstract ideas held to be non-statutory by the courts (see Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307 (Fed. Cir. 2016)—receiving, screening, and distributing e-mail, similar because at another level of abstraction the claims could be characterized as receiving, screening, and classifying text segments from a document; Electric Power Grp., LLC v. Alstom S.A., 830 F.3d 1350 (Fed. Cir. 2016)—process of gathering and analyzing information of a specified content, then displaying the results, similar because at another level of abstraction the claims could be characterized as process of gathering and analyzing information from a document, then generating the results in a skill assessment; Intellectual Ventures I LLC v. Capital One, 850 F.3d 1332 (Fed. Cir. 2017)—organizing, displaying, and manipulating data of particular (XML) documents, similar because at another level of abstraction the claims could be characterized as recognizing, tagging, and manipulating data of particular documents; University of Florida Research Foundation v. GE Company, 916 F.3d 1363 (Fed. Cir. 2019)—collecting, analyzing, manipulating (including converting into a different format), and displaying data, which also characterizes the invention; In re: Killian, No. 2021-2113, Fed. Cir., Aug. 23, 2022)—collecting information, understanding that information, and determining eligibility for benefits, similar because at another level of abstraction the claims could be characterized as collecting information, understanding that information, and determining eligibility for a skill category). See also Intellectual Ventures I LLC v. Capital One Fin. Corp., 850 F.3d 1332, 1340 (Fed. Cir. 2017) (discussing abstract idea precedent related to the collection, recognition, manipulation, and storage of data)
These cases describe significantly similar aspects of the claimed invention, albeit at another level of abstraction. See Apple, Inc. v. Ameranth, Inc., 842 F.3d 1229, 1240-41 (Fed. Cir. 2016) ("An abstract idea can generally be described at different levels of abstraction. As the Board has done, the claimed abstract idea could be described as generating menus on a computer, or generating a second menu from a first menu and sending the second menu to another location. It could be described in other ways, including, as indicated in the specification, taking orders from restaurant customers on a computer.").
MPEP 2106 Step 2A – Prong 2:
This judicial exception is not integrated into a practical application because there are no meaningful limitations that transform the exception into a patent eligible application. The elements merely serve to provide a general link to a technological environment (e.g., computers and the Internet) in which to carry out the judicial exception (server; memory; one or more processors coupled to the memory; non-transitory, computer-readable storage medium storing one or more sequences of instructions; transformer-based machine learning (ML) models; reinforcement learning model—all recited at a high level of generality).
Although they have and execute instructions to perform the abstract idea itself (e.g., modules, program code, etc. to automate the abstract idea), this also does not serve to integrate the abstract idea into a practical application as it merely amounts to instructions to "apply it." Aside from such instructions to implement the abstract idea, they are solely used for generic computer operations (e.g., receiving, storing, retrieving, transmitting data), employing the computer as a tool. See FairWarning IP, LLC v. Iatric Sys., Inc., 839 F.3d 1089, 1096 (Fed. Cir. 2016) ("[T]he use of generic computer elements like a microprocessor or user interface do not alone transform an otherwise abstract idea into patent-eligible subject matter.") (citing DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245,1256 (Fed. Cir. 2014)) (emphasis added).
The claims only manipulate abstract data elements into another form. They do not set forth improvements to another technological field or the functioning of the computer itself and instead use computer elements as tools to improve the functioning of the abstract idea identified above. Looking at the additional limitations and abstract idea as an ordered combination and as a whole 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. Rather than any meaningful limits, their collective functions merely provide generic computer implementation of the abstract idea identified in Prong One. None of the additional elements recited "offers a meaningful limitation beyond generally linking 'the use of the [method] to a particular technological environment,' that is, implementation via computers." Alice Corp., slip op. at 16 (citing Bilski v. Kappos, 561 U.S. 610, 611 (U.S. 2010. See also Recentive Analytics, inc. v. Fox. Corp., Fed Cir. No. 2023-2437 (Apr. 18, 2025), slip op. at 13 ("[T]he only thing the claims disclose about the use of machine learning is that machine learning is used in a new environment.").
At the levels of abstraction described above, the claims do not readily lend themselves to a finding that they are directed to a nonabstract idea. Therefore, the analysis proceeds to step 2B. See BASCOM Global Internet v. AT&T Mobility LLC, 827 F.3d 1341, 1349 (Fed. Cir. 2016) ("The Enfish claims, understood in light of their specific limitations, were unambiguously directed to an improvement in computer capabilities. Here, in contrast, the claims and their specific limitations do not readily lend themselves to a step-one finding that they are directed to a nonabstract idea. We therefore defer our consideration of the specific claim limitations’ narrowing effect for step two.") (citations omitted).
MPEP 2106 Step 2B:
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception for the same reasons as presented in Step 2A Prong 2 (i.e., they amount to nothing more than a general link to a particular technological environment and instructions to apply it there). Moreover, the additional elements recited are known and conventional computing elements (server; memory; one or more processors coupled to the memory; non-transitory, computer-readable storage medium storing one or more sequences of instructions; transformer-based machine learning (ML) models; reinforcement learning model—see Specification ¶¶ 0035, 43, 46, 70, 81 describing these at a high level of generality and in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy the statutory disclosure requirements).
The Federal Circuit has recognized that "an invocation of already-available computers that are not themselves plausibly asserted to be an advance, for use in carrying out improved mathematical calculations, amounts to a recitation of what is 'well-understood, routine, [and] conventional.'" SAP Am., Inc. v. InvestPic, LLC, 890 F.3d 1016, 1023 (Fed. Cir. 2018) (alteration in original) (citing Mayo v. Prometheus, 566 U.S. 66, 73 (2012)). Apart from the instructions to implement the abstract idea, they only serve to perform well-understood functions (e.g., receiving, storing, retrieving, transmitting data—see Specification above as well as Alice Corp.; Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307 (Fed. Cir. 2016); and Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334 (Fed. Cir. 2015) covering the well-known nature of these basic computer functions).
"The use and arrangement of conventional and generic computer components recited in the claims—such as a database, user terminal, and server— do not transform the claim, as a whole, into 'significantly more' than a claim to the abstract idea itself. We have repeatedly held that such invocations of computers and networks that are not even arguably inventive are insufficient to pass the test of an inventive concept in the application of an abstract idea." Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1056 (Fed. Cir. 2017) (citations and quotation marks omitted). 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.
Dependent Claims Step 2A:
The limitations of the dependent claims but for those addressed below merely set forth further refinements of the abstract idea without changing the analysis already presented (i.e., they merely narrow the abstract idea without adding any new additional elements beyond it). Additionally, for the same reasons as above, the limitations fail to integrate the abstract idea into a practical application because they use the same general technological environment and instructions to implement the abstract idea as the independent claims. Claim 5 recites permuted language modeling and claims 7 and 16 recite using a multilevel perceptron as a fourth ML model. However, similar to the machine learning limitations in the independent claims, these are generic tools. Rather than improving their technical abilities in a meaningful way, the invention is merely using them in a new abstract environment.
Dependent Claims Step 2B:
The dependent claims merely use the same general technological environment and instructions to implement the abstract idea. Although they add the elements identified in 2A above (permuted language modeling, using a multilevel perceptron as a fourth ML model), these do not amount to significantly more for the same reasons they fail to integrate the abstract idea into a practical application. Moreover, the Specification also indicates this is the routine use of known components for the same reasons presented with respect to the elements in the independent claims above (see ¶¶ 0043-44 describing these at a high level and without appreciable technical detail). Accordingly, they are not directed to significantly more than the exception itself, and are not eligible subject matter under § 101.
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 DANIEL VETTER whose telephone number is (571)270-1366. The examiner can normally be reached M-F 9:00-6:00.
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/DANIEL VETTER/Primary Examiner, Art Unit 3628