Ex parte Shao

• Docket Number: Appeal 2022-003386,Application 16/556,221,Technology Center No. 3600
• Decision Date: 31 October 2023
• Parties: Ex parte EDWIN H. SHAO, SPENCER WHITNEY YING, KIN CHUNG ROGER SO, and KIRILL PAVLOV
• Court: Patent Trial and Appeal Board

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Ex parte EDWIN H. SHAO, SPENCER WHITNEY YING, KIN CHUNG ROGER SO, and KIRILL PAVLOV

Appeal No. 2022-003386

Application No. 16/556,221

Technology Center No. 3600

United States Patent and Trademark Office, Patent Trial and Appeal Board

October 31, 2023

FILING DATE: 08/29/2019

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Before ROBERT E. NAPPI, LARRY J. HUME, and JOYCE CRAIG, Administrative Patent Judges.

DECISION ON APPEAL

HUME, Administrative Patent Judge.

Pursuant to 35 U.S.C. § 134(a), Appellant^[1] appeals from the Examiner's decision to reject claims 1-13 and 15-20. See Non-Final Act. 1. We have jurisdiction under 35 U.S.C. § 6(b).

We AFFIRM.

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STATEMENT OF THE CASE^[2]

The claimed subject matter is directed to systems and methods for recruitment candidate equity modeling. See Spec. (Title). In particular, Appellant's disclosed embodiments and claimed invention relate to "systems and method[s] for a comprehensive system that allows a recruitment firm to award billings based on various pipeline activities that a recruiter can perform to improve the likelihood their candidate will become a placement." Spec. ¶1.

Claim 1, reproduced below, is representative of the subject matter on appeal:

1. A computer-implemented method for modeling candidate equity comprising

registering a plurality of candidates in a candidate database

generating a profile for each candidate and storing the profiles in the candidate database;

submitting a candidate to one or more job positions, based on the candidate profile, wherein the one or more job positions are associated with one or more clients;

assigning a recruitment stage parameter to each submitted candidate, based on state of the candidate in a recruiting pipeline, wherein the recruiting pipeline comprises a plurality of recruitment stages;

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for each recruitment stage, computing a transition percentage as the ratio between the number of candidates reaching the next stage and the number of candidates reaching the current stage;

storing the assigned recruitment stage parameter in an equity model database;

storing in the equity model database an identifier of a recruiter associated with the candidate, obtained from a recruiter database;

tracking, in the equity model database, a plurality of candidates in the recruiting pipeline, wherein tracking comprises updating the assigned recruitment stage parameter for each submitted candidate in the equity model database, based on state of the candidate in the recruiting pipeline;

for each candidate, generating in an analytics module comprising a machine learning model, a transition likelihood, comprising a likelihood of the candidate transitioning from a current stage between stages of the recruiting pipeline to a next stage of the recruiting pipeline, wherein the transition likelihood is generated, at least in part, based on the transition percentage and an amount of time the candidate has spent in the current stage of the pipeline, wherein the transition likelihood decreases exponentially by a given percentage each day, the percentage calculated from historical data including the median and standard deviation of past transition times;

for each candidate, generating by the machine learning model, a placement likelihood corresponding to likelihood that the candidate will be placed in the position based on inputting to the machine learning model a plurality of features including the current stage of the candidate in the recruiting pipeline, wherein the machine learning model is trained based on a dataset of training examples each comprising the plurality of features and a placement label, the placement label comprising an indication of whether a corresponding candidate was placed, wherein the plurality of features comprise time in the stage, seniority of the candidate, resume text, and expected salary of the position;

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for each candidate, adjusting the placement likelihood by a depreciation amount comprising a staleness parameter, the staleness parameter determined by the length of time since the last change in the candidate's current stage;

generating, in the analytics module, a candidate equity based on the placement likelihood and an expected placement value associated with the client;

calculating the difference between the candidate equity at a first time and the candidate equity at a second time;

generating user interface data, for display in a user interface, based at least in part on at least one of:

the candidate equity and the calculated difference; and

displaying a dashboard user interface, the dashboard user interface comprising a candidate assets portion and an active candidates portion, wherein the candidate assets portion depicts a count value of multiple status for candidates, and wherein the active candidates portion depicts a listing of a plurality of active candidates, the active candidates portion comprising a candidate name, a status of the active candidate, and a value of the candidate equity value.

REJECTION

The Examiner maintains the following rejection:

Claim(s) Rejected	35 U.S.C. §	Reference(s)/ Basis
1-13, 15-20	101	Eligibility

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CLAIM GROUPING

Based on Appellant's arguments (Appeal Br. 10-21) and our discretion under 37 C.F.R. § 41.37(c)(1)(iv), we decide the appeal of subject matter eligibility rejection of claims 1-13 and 15-20 under 35 U.S.C. § 101 on the basis of representative claim l.^[3]

ISSUE

Appellant argues (Appeal Br. 10-20) the Examiner's rejection of claim 1 under 35 U.S.C. § 101 as being directed to patent-ineligible subject matter is in error. These contentions present us with the following issue:

Under the USPTO's Revised Guidance, informed by our governing case law concerning 35 U.S.C. § 101, is claim 1 patent-ineligible under § 101?

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PRINCIPLES OF LAW

A. 35 U.S.C. §101

An invention is patent-eligible if it is a "new and useful process, machine, manufacture, or composition of matter." 35 U.S.C. § 101.^[4]However, the Supreme Court has long interpreted 35 U.S.C. § 101 to include implicit exceptions: "[l]aws of nature, natural phenomena, and abstract ideas" are not patentable. Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 70 (2012) (brackets in original) (citing Diamond v. Diehr, 450 U.S. 175,185(1981)).

In determining whether a claim falls within an excluded category, we are guided by the Supreme Court's two-step framework, described in Mayo and Alice. Alice Corp. v. CLS Banklnt'l, 573 U.S. 208, 217-18 (2014) (citing Mayo, 566 U.S. at 75-77). In accordance with that framework, we first determine what concept the claim is "directed to." See Alice, 573 U.S. at 219 ("On their face, the claims before us are drawn to the concept of intermediated settlement, i.e., the use of a third party to mitigate settlement risk"); see also Bilski v. Kappos, 561 U.S. 593, 611 (2010) ("Claims 1 and4 in petitioners' application explain the basic concept of hedging, or protecting against risk . . . .").

Concepts determined to be abstract ideas, and thus patent ineligible, include certain methods of organizing human activity, such as fundamental

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economic practices (Alice, 573 U.S. at 219-20; Bilski, 561 U.S. at 611); mathematical formulas (Parker v. Flook, 437 U.S. 584, 594-95 (1978)); and mental processes (Gottschalk v. Benson, 409 U.S. 63, 67 (1972)). Concepts determined to be patent eligible include physical and chemical processes, such as "molding rubber products" (Diehr, 450 U.S. at 191); "tanning, dyeing, making water-proof cloth, vulcanizing India rubber, smelting ores" (id. at 182 n.7 (quoting Corning v. Burden, 56 U.S. 252, 267-68 (1853))); and manufacturing flour (Benson, 409 U.S. at 69 (citing Cochrane v. Deener, 94 U.S. 780, 785 (1876))).

Abstract ideas may include, but are not limited to, fundamental economic practices, methods of organizing human activities, and mathematical formulas or relationships. Alice, 573 U.S. at 217-21. Under this guidance, we must therefore ensure at step one that we articulate what the claims are directed to with enough specificity to ensure the step one inquiry is meaningful. Id. at 217 ("[W]e tread carefully in construing this exclusionary principle lest it swallow all of patent law.").

Examples of claims that do not recite mental processes because they cannot be practically performed in the human mind include: (a) a claim to a method for calculating an absolute position of a GPS receiver and an absolute time of reception of satellite signals, where the claimed GPS receiver calculated pseudoranges that estimated the distance from the GPS receiver to a plurality of satellites, SiRF Technology, Inc. v. International Trade Commission, 601 F.3d 1319, 1331-33 (Fed. Cir. 2010); (b) a claim to detecting suspicious activity by using network monitors and analyzing network packets, SRI Int'l, Inc. v. Cisco Systems, Inc., 930 F.3d 1295, 1304 (Fed. Cir. 2019); (c) a claim to a specific data encryption method for

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computer communication involving a several-step manipulation of data, Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1149 (Fed. Cir. 2016) (distinguishing TQP Development, LLC v. Intuit Inc., 2014 WL 651935 (E.D. Tex. Feb. 19, 2014)) (the specific data encryption method "could not conceivably be performed in the human mind or with pencil and paper"). Whereas a claim limitation to a process that "can be performed in the human mind, or by a human using a pen and paper" qualifies as a mental process, a claim limitation that "could not, as a practical matter, be performed entirely in a human's mind" (even if aided with pen and paper) would not qualify as a mental process.^[5]

In Diehr, the claim at issue recited a mathematical formula, but the Supreme Court held "[a] claim drawn to subject matter...