Microsoft Technology Licensing, LLC

Patent Trials and Appeals Board

Mar 16, 2021

2020006569 (P.T.A.B. Mar. 16, 2021)

UNITED STATES PATENT AND TRADEMARK OFFICE
UNITED STATES DEPARTMENT OF COMMERCE
United States Patent and Trademark Office
Address: COMMISSIONER FOR PATENTS
P.O. Box 1450
Alexandria, Virginia 22313-1450
www.uspto.gov
APPLICATION NO. FILING DATE FIRST NAMED INVENTOR ATTORNEY DOCKET NO. CONFIRMATION NO.
15/660,779 07/26/2017 Keqing Liang 3080.I56US1 1302
45839 7590 03/16/2021
SCHWEGMAN LUNDBERG & WOESSNER / LINKEDLN/MICROSFT
PO BOX 2938
MINNEAPOLIS, MN 55402
EXAMINER
WHITAKER, ANDREW B
ART UNIT PAPER NUMBER
3629
NOTIFICATION DATE DELIVERY MODE
03/16/2021 ELECTRONIC
Please find below and/or attached an Office communication concerning this application or proceeding.
The time period for reply, if any, is set in the attached communication.
Notice of the Office communication was sent electronically on above-indicated "Notification Date" to the
following e-mail address(es):
USPTO@slwip.com
slw@blackhillsip.com
PTOL-90A (Rev. 04/07)

UNITED STATES PATENT AND TRADEMARK OFFICE
____________

BEFORE THE PATENT TRIAL AND APPEAL BOARD
____________

Ex parte KEQING LIANG, VIBHU PRAKASH SAXENA, and
JASON PHAN

Appeal 2020-006569
Application 15/660,779
Technology Center 3600
____________

Before RICHARD M. LEBOVITZ, FRANCISCO C. PRATS, and
JEFFREY N. FREDMAN, Administrative Patent Judges.

LEBOVITZ, Administrative Patent Judge.

DECISION ON APPEAL
The Examiner rejected the claims under 35 U.S.C. § 103 as obvious.
Pursuant to 35 U.S.C. § 134(a), Appellant1 appeals from the Examiner’s
decision to reject the claims. We have jurisdiction under 35 U.S.C. § 6(b).
We REVERSE but set forth a new ground of rejection pursuant to 37
C.F.R. § 41.50(b).

1 We use the word “Appellant” to refer to “applicant” as defined in 37
C.F.R. § 1.42. Appellant identifies the real party in interest as Microsoft
Technology Licensing, LLC. Appeal Br. 2.
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STATEMENT OF THE CASE
The Examiner rejected claims 1–20 as follows:
Claims 1–11 and 14–20 under 35 U.S.C. § 103 as obvious in view of
Novack (US 2009/0299993 A1, published Dec. 3, 2009) (“Novack”) and
Obernikhin et al. (US 2014/0317079 A1, published Oct. 23, 2014)
(“Obernikhin”). Final Act. 4.
Claims 12 and 13 under 35 U.S.C. § 103 as obvious in view of
Novack, Obernikhin, and Chevalier et al. (US 2015/0127565 A1, published
May 7, 2015) (“Chevalier”). Final Act. 10.
The obviousness rejections are reversed. However, as explained in
more detail below, we set forth a new ground of rejection pursuant to 37
C.F.R. § 41.50(b) of claims 1, 14, and 20 under 35 U.S.C. § 101 as lacking
patent eligibility. We leave it up to the Examiner to consider the remaining
claims. The PTAB serves as a board of review, not a de novo examination
tribunal. See 35 U.S.C. 6(b).
There are three independent claims on appeal, claims 1, 14, and 20.
Claim 1 is directed to a system for executing a method, claim 14 to a
computer-implemented method, and claim 20 to a computer readable
medium storing the instructions to carry out a method. The same method
steps are recited in all three claims. We select claim 1 as representative. The
claim is reproduced below with bracketed annotations added to number the
claim limitations.
1. A computer system, comprising:
[1] a processor;
[2] a storage device;
[3] a candidate predictor engine; and
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[4] a memory device holding an instruction set executable on
the processor to cause the computer system to perform
operations comprising:
[5] encoding, by the candidate predictor engine, data
representing an applicant quality (AQ) score for each
job/applicant pair for a plurality of applicants to a job posting,
the AQ score being based on an AQ model;
[6] storing, on the storage device, the encoded data
representing the AQ scores for each job/applicant pair for the
plurality of applicants to the job posting;
[7] assigning member-level weights to each of the
plurality of applicants;
[8] calculating, by the candidate predictor engine,
weighted AQ scores for each of the job/applicant pairs, the
weighted AQ scores being products of respective AQ scores
retrieved from the storage device and member-level weights;
[9] summing the weighted AQ scores to derive a total
weighted score for the job posting;
[10] generating, by the candidate predictor engine, a job-
level probability of confirmed hire (pCH) based on the total
weighted score, the job-level pCH indicating a likelihood of the
job posting being filled by an applicant; and
[11] transmitting the job-level pCH to a client device for
display.

OBVIOUSNESS REJECTIONS
Rejection
The Examiner found that Novack describes a system comprising a
processor, storage device, and memory device as recited in claim 1
(limitations 1, 2, 4). Final Act. 4. The Examiner also found that Novack
describes a software “engine” (the “[3] candidate predictor engine” of claim
1) that performs steps 5–9 of claim 1. Final Act. 4–5. The Examiner stated
that Novack does not disclose generating “a job-level probability of
confirmed hire (pCH) based on the total weighted score” as recited in step
10 of claim 1. Final Act. 5. However, the Examiner found that Obernikhin
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describes step 10 of the claim. Id. The Examiner determined it would have
been obvious to one of ordinary skill in the art at the time of the effective
filing date of the invention to use Obernikhin’s method of job recruitment in
Novack “to perform fuzzy logic to determine a culture fit with an
organization.” Final Act. 5–6. The Examiner stated that “culture fit” is “a
problem that is often missed by someone out of the recruitment industry.”
Final Act. 6. The Examiner explained:
[E]xperienced recruiters know that the probability of a
particular candidate to be hired by a particular hiring manager is
significantly higher if the candidate and the hiring manager
have graduated from the same educational institution or worked
in the same set of companies in the past, or grown up in the
same geographical area, or (in case of software developers)
participated in the same open-source project.
Final Act. 6.
Discussion
Claim 1 requires that AQ scores are encoded for applicants “to a job
posting” (step 5). Appellant argues that Novack does not use job postings,
but rather collects lists of candidates that an employer can search through
and decide whether to contact a candidate. Appeal Br. 12–13. Based on the
following disclosure from Novack, Appellant argues that Novack teaches
away from job postings:
The service enables employers and recruiters acting on
behalf of employers to view candidate profiles, filter and/ or
search the profiles according to the data available in the
profiles, and input criteria for evaluating candidates based on
the candidates' quantitative assessments. For example, the
service determines scores for the candidates based on the
employer criteria and quantitative assessments, where a score
assigned to a candidate represents the likelihood that the
candidate will succeed in a particular career role or position.
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The service returns a list of the candidates ranked according to
their scores, and from the list, an employer can quickly and
easily locate the presumably most qualified candidates, and
contact them through service. Thus, the candidate recruiting
service can provide a broader pool of initial candidates than
that obtained using job postings and other conventional
recruiting methods and also help employers to narrow down a
pool of candidates in an efficient and intelligent manner.
Novack ¶ 19 (emphasis added).
While Novack describes its method as an improvement over the use of
job postings, Appellant has not pointed to anything in the publication that
would preclude applying Novack’s scoring method to job postings. “[J]ust
because better alternatives exist in the prior art does not mean that an
inferior combination is inapt for obviousness purposes.” In re Mouttet, 686
F.3d 1322, 1334 (Fed. Cir. 2012). A “finding that the prior art as a whole
suggests the desirability of a particular combination need not be supported
by a finding that the prior art suggests that the combination claimed by the
patent applicant is the preferred, or most desirable, combination.” In re
Fulton, 391 F.3d 1195, 1200 (Fed. Cir. 2004). Thus, while using job
postings is less preferred and is described by Novack as inferior, it was still
described by Novack as an alternative, albeit one that Novack has improved
upon. “[A] reference may teach away from a use when that use would render
the result inoperable.” In re ICON Health & Fitness, Inc., 496 F.3d 1374,
1381 (Fed. Cir. 2007). In this case, even if using job postings is inferior and
less desirable for the reasons stated by Novack, Appellant did not establish
that applying Novack and Obernikhin to “job postings” would have been
inoperable.
Appellant also argues that neither Novack nor Obernikhin, alone or in
combination, disclose or suggest step 9 of claim 1 of “summing the weighted
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AQ scores to derive a total weighted score for the job posting.” Appeal Br.
14–15 (emphasis added). Appellant states that Novack “simply describe how
different assessment scores for one candidate may be combined to generate a
score that corresponds to ‘the likelihood of the candidate [] to match the
career role’.” Appeal Br. 15. Appellant emphasizes that the “calculation
described in Novack involves averaging several scores for ONE candidate,
to arrive at a final score for the candidate,” and not a total weight score the
job posting as required by the claim. Id.
We agree with Appellant that the Examiner erred in finding that step 9
of claim 1 is met by the combination of Novack and Obernikhin. The
Examiner cited paragraphs 67–70 and 81 of Novack as meeting the claim
limitation. Final Act. 5; Ans. 6. Paragraphs 69 and 70 determine a score for a
candidate which can be adjusted based on weightings assigned by an
employer. Novack teaches that these scores “correspond to the likelihood of
the candidate 118 to match the career role or employment position offered
and defined by the employer 117.” Novack ¶ 70. However, there is no
disclosure in paragraphs 67–70 of Novack of summing the scores of the
candidates as required by step 10 of the claim. Paragraph 81 of Novack
teaches aggregating data: “platform 112 aggregates information from the
candidate profiles, and from the information, aggregates statistics and
derives further data which may be sold to employers 117, recruiters 120,
career counselors 122, and third parties that are not registered with the
recruiting service.” However, this disclosure does not teach summing the
scores of candidates as required by step 9 of claim 1, and the Examiner did
not explain how the disclosure would reasonably suggest this claim
limitation. Novack teaches using the aggregated data for “targeted direct
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marketing lists” (Novack ¶ 81), but does not sum it for the purpose of step
10 of “generating, by the candidate predictor engine, a job-level probability
of confirmed hire (pCH) based on the total weighted score.”
The Examiner did not establish that Obernikhin makes up for this
deficiency in Novack. The Examiner found that Obernikhin describes step
10 of the claim, identifying paragraph 56 for support. Final Act. 5.
Paragraph 56 of Obernikhin describes a system which “can rank search
results according to the probability of a candidate responding to a job offer
by the recruiter.” This probability is further described in paragraph 57.
However, each of these paragraphs describe the probability of a single
candidate accepting a job and not the probability of getting a confirmed hire
for the job posting as required by step 10 of the rejected claim.
Accordingly, for the reason described above, we conclude that the
Examiner erred in rejecting claim 1 as obvious in view of Novack and
Obernikhin. Claims 2–11 and 14–20 comprise the same claim limitation
found to be deficient in Novack and Obernikhin and are reversed for the
same reasons.

Chevalier
The Examiner further cited Chevalier for the additional limitations
recited in dependent clams 12 and 13. Claims 12 and 13 depend from claim
1 and further comprise “wherein the operations further comprise
instantiating a plurality of job candidate decision trees.” The Examiner
found that Chevalier meets these additional limitations. Final Act. 10–11.
The Examiner did not find that Chevalier describes or suggests the
deficiencies discussed above in the combination Novack and Obernikhin.
Consequently, the obviousness rejection of claims 12 and 13 is reversed.
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NEW GROUND OF REJECTION
We enter a new ground of rejection and reject claims 1, 14, and 20 as
patent-ineligible under 35 U.S.C. § 101.

PATENT ELIGIBILITY
Principles of Law
Under 35 U.S.C. § 101, an invention is patent-eligible if it claims a
“new and useful process, machine, manufacture, or composition of matter.”
However, not every discovery is eligible for patent protection. Diamond v.
Diehr, 450 U.S. 175, 185 (1981). “Excluded from such patent protection are
laws of nature, natural phenomena, and abstract ideas.” Id. The Supreme
Court articulated a two-step analysis to determine whether a claim falls
within an excluded category of invention. Alice Corp. v. CLS Bank Int’l, 573
U.S. 208 (2014); Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566
U.S. 66, 75–77 (2012).
In the first step, it is determined “whether the claims at issue are
directed to one of those patent-ineligible concepts.” Alice, 573 U.S. at 217. If
it is determined that the claims are directed to an ineligible concept, then the
second step of the two-part analysis is applied in which it is asked “[w]hat
else is there in the claims before us?” Id. (alteration in original) (citation and
quotation marks omitted). The Court explained that this step involves
a search for an “‘inventive concept’”—i.e., an element or
combination of elements that is “sufficient to ensure that the
patent in practice amounts to significantly more than a patent
upon the [ineligible concept] itself.”
Alice, 573 U.S. at 217–18 (alteration in original) (citing from Mayo, 566
U.S. at 75–77).
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Alice, relying on the analysis in Mayo of a claim directed to a law of
nature, stated that in the second part of the analysis, “the elements of each
claim both individually and ‘as an ordered combination’” must be
considered “to determine whether the additional elements ‘transform the
nature of the claim’ into a patent-eligible application.” Alice, 573 U.S. at 217
(citation omitted).
The PTO published revised guidance on the application of 35 U.S.C.
§ 101, USPTO’s January 7, 2019 Memorandum, 2019 Revised Patent
Subject Matter Eligibility Guidance, 84 Fed. Reg. 50 (Jan. 7, 2019) (“2019
Eligibility Guidance”) (throughout this decision, we cite to the Federal
Register where the 2019 Eligibility Guidance is published). This guidance
provides additional direction on how to implement the two-part analysis of
Mayo and Alice.
Step 2A, Prong One, of the 2019 Eligibility Guidance, looks at the
specific limitations in the claim to determine whether the claim recites a
judicial exception to patent eligibility. In Step 2A, Prong Two, the claims are
examined to identify whether there are additional elements in the claims that
integrate the exception in a practical application, namely, is there a
“meaningful limit on the judicial exception, such that the claim is more than
a drafting effort designed to monopolize the judicial exception.” 84 Fed.
Reg. at 54 (Prong Two).
If the claim recites a judicial exception that is not integrated into a
practical application, then as in the Mayo/Alice framework, Step 2B of the
2019 Eligibility Guidance instructs us to determine whether there is a
claimed “inventive concept” to ensure that the claims define an invention
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that is significantly more than the ineligible concept itself. 84 Fed. Reg. at
56.
With these guiding principles in mind, we proceed to determine
whether the claimed subject matter in this appeal is eligible for patent
protection under 35 U.S.C. § 101.
Discussion
Claim 1 is directed to a “system” that comprises a processor, storage
device, and memory device that generates a probability of confirmed hire for
a job posting. A system is a “manufacture,” one of the broad statutory
categories of patent-eligible subject matter under 35 U.S.C. § 101.
Therefore, we find that the claim is directed to a statutory class of invention,
and proceed to Step 2A, Prong One, of the Eligibility Guidance.

Step 2A, Prong One
In Step 2A, Prong One, of the 2019 Eligibility Guidance, the specific
limitations in the claim are examined to determine whether the claim recites
a judicial exception to patent eligibility, namely, whether the claim recites an
abstract idea, law of nature, or natural phenomenon. The 2019 Eligibility
Guidance directs us to search each limitation in the claim to determine
whether it recites abstract a judicial exception. 84 Fed. Reg. at 54.
The computer system comprises a processor, storage device, candidate
predictor engine, and a memory device (limitations 1–4). The memory
device holds instructions for execution on the processor. The instructions
comprise steps 5–11 of the claim. The purpose of the claim is to determine
the probability that a job posting will be filled by an applicant for a job. The
claim therefore relates to “managing . . . interactions between people,” one
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of the examples of the abstract idea of “certain methods of organizing
human activity” listed in the 2019 Eligibility Guidance (84 Fed. Reg. at 52)
because hiring applicants for a job by an employer is an interaction between
the applicant and employer. We also find, as explained below, that several of
the steps in the method of organizing human activity can be accomplished in
the human mind and also involve mathematical calculations. Therefore the
claim also recites the abstract idea of mental processes and mathematical
concepts, both of which are groupings of abstract ideas listed in the 2019
Eligibility Guidance. 84 Fed. Reg. at 52.
In the first step of the method, step 5, data representing the applicant
quality score (AQ) is encoded for each job/applicant pair for “plurality of
applicants to a job posting.” The AQ scores are stored on a storage device
(step 6). The claim recites that the AQ score is based on an “AQ model,” but
doesn’t identify the model or explain how the model is used to determine the
“quality” of the applicant. The Specification identifies some of the features
used in the model and states that a “random forest model” can used,2 but the
claim is not limited to the disclosed examples or model. We find that this
step could be accomplished mentally in the human mind, by the human

2 The Specification describes some of the features used to determine the AQ
score: “In some embodiments, the AQ model uses standardized features
from member profiles (e.g., profile attributes for a profile of a member of a
professional social network service) and standardized features from job
descriptions to train a random forest model. Examples of job features
include function, industry, geographic location of job (e.g., country, state,
province, region, or city), and organization size (e.g., small, medium, or
large company size). Examples of member profile features include seniority
(e.g., years of experience), skills, title/supertitle, and geographic location of
member (e.g., residence or citizenship country, work visa country, residence
state, residence province, residence region, or residence city).” Spec. ¶ 34.
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determining what applicant attributes are important to the job, and assigning
them a value, based on whether the job applicant possesses them, to arrive at
a quality score.
“[M]ember-level weights” are assigned to each job applicant (step 7).
The claim does recite how these weight assignments are made. The Appeal
Brief (Appeal Br. 6) cites the following disclosure as support for this
limitation: “member-level weights are assigned to applicants with higher AQ
scores (i.e., applicants having AQ scores that are greater than other
applicants’ AQ scores)” (Spec. ¶ 67). But this disclosure does not explain
how specific values for each applicant are determined. We find that this step
could be performed mentally by a human, for example, where a human
decides to give more weight to each of the applicants with the ten highest
AQ scores.
In the next step of the claim, “weighted AQ scores” are calculated for
each of the job/applicant pairs by multiplying the AQ score and the member-
level weight (“being products” of the “AQ score[]” and the “member-level
weights” (step 8). The weighted AQ scores are summed “to derive a total
weighted score for the job posting” (step 9). Both steps 8 and 9 are
mathematical calculations and therefore are abstract ideas.
A job-level probability of confirmed hire (pCH) based on the total
weighted score is generated (step 10). The claim does not explain how the
pCH is generated; it only states that the pCH indicates “a likelihood of the
job posting being filled by an applicant.” This value is displayed on a client
device (step 11).
The Specification explains how the pCH is useful:
Based on the job-level pCH value (i.e., score), the job poster
can decide whether to take some action. For example, if the job-
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level pCH indicates a relatively low probability or low
likelihood of the job being filled by a qualified applicant, the
job poster may interact with a user interface at the client device
to relax (i.e., lower) the job requirements or reduce the desired
skills for the job posting.
Spec. ¶ 70.
This step could be done mentally where a high score in step 9 is
identified as a high probability of getting the job filled and a low score
identified as a low probability of filling the job.
In sum, for a specific job listing, an AQ score for each application is
encoded, which is multiplied by a member-level weight to obtain a weight
AQ score. The weighted AQ scores are added up for all applicants to obtain
a total weighted score which is used to generate a likelihood of the job
posting being filled by an applicant. As explained above, we find that each
of steps 5 and 7–10 comprise an abstract idea and are a part of the method of
organizing human activity.

Step 2A, Prong Two
Step 2A, Prong Two, examines whether there are additional elements
in the claims that integrate the exception in a practical application, namely,
is there a “meaningful limit on the judicial exception, such that the claim is
more than a drafting effort designed to monopolize the judicial exception.”
84 Fed. Reg. at 54 (Prong Two).
As explained above, steps 5 and 7–10 represent the abstract idea in the
claim and are not “additional elements” beyond the judicial exception. The
issue is therefore whether the additional elements recited in the claim,
including limitations 1–4, 6, and 11, are sufficient to integrate the abstract
idea into a practical application.
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We do not find any evidence from the Specification that the recited
processor (limitation 1), storage device (limitation 2), and memory device
(limitation 4) are anything more than generic computer components. The
“candidate predictor engine” is the software that performs steps 5–10 of the
claim. The method steps of claim 1 are therefore carried out using generic
components performing their known and established functions. The claimed
computer system is merely automating what could be done by a human with
no improvement to the system, itself. “Steps that do nothing more than spell
out what it means to ‘apply it on a computer’ cannot confer patent-
eligibility. Alice, 134 S.Ct. at 2359.” Intellectual Ventures I LLC v. Capital
One Bank (USA), 792 F.3d 1363, 1370–71 (Fed. Cir. 2015); see also Credit
Acceptance Corp. v. Westlake Servs., 859 F.3d 1044, 1055 (Fed. Cir. 2017)
(“mere automation of manual processes using generic computers does not
constitute a patentable improvement in computer technology.”).
Transmitting the pCH for display to a human, as recited in the last
step of the claim, is “insignificant extra-solution activity” and therefore not
sufficient to impart eligibility on the claim by integrating the judicial
exception into a practical application. 84 Fed. Reg. at 55.
We also must “look to whether the claims . . . focus on a specific
means or method that improves the relevant technology or are instead
directed to a result or effect that itself is the abstract idea and merely invoke
generic processes and machinery.” McRO, Inc. v. Bandai Namco Games Am.
Inc., 837 F.3d 1299, 1314 (Fed. Cir. 2016). Dropbox, Inc. v. Synchronoss
Techns., Inc., 815 Fed. Appx. 529, 533 (Fed. Cir. 2020) (non-precedential),
further explained:
The patent has to describe how to solve the problem in a
manner that encompasses something more than the “principle in
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the abstract.” See [ChargePoint, Inc. v. SemaConnect, Inc., 920
F.3d 759, 769 (Fed. Cir. 2019)] (explaining that an invention
may not be patent eligible if the “claims ‘were drafted in such a
result-oriented way that they amounted to encompassing the
‘principle in the abstract’ no matter how implemented’”
(quoting Interval Licensing LLC v. AOL, Inc., 896 F.3d 1335,
1343 (Fed. Cir. 2018))).
Dropbox, 815 Fed. Appx. at 533.
The steps for determining the pCH are recited in a “result-oriented
way.” Specifically, the claim does not recite how the AQ score is encoded
(step 5), how the member-level weights are assigned (step 7), nor how the
pCH is generated based on these values (step 10). These steps state the
desired result, but not how the result is accomplished. Steps 8 and 9 involve
performing tax calculations with no specific implementation recited to
perform the calculations. Consequently, the claimed steps encompass the
principle of generating a job-level probability of a confirmed hire in the
abstract. There is no additional element in the claim beyond the judicial
exception which integrates the abstract idea into a practical application. We
thus proceed to Step 2B of the analysis.

Step 2B
Step 2B of the Eligibility Guidance asks whether there is an inventive
concept. In making this Step 2B determination, we must consider whether
there are specific limitations or elements recited in the claim “that are not
well-understood, routine, conventional activity in the field, which is
indicative that an inventive concept may be present” or whether the claim
“simply appends well-understood, routine, conventional activities previously
known to the industry, specified at a high level of generality, to the judicial
exception, which is indicative that an inventive concept may not be present.”
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84 Fed. Reg. at 56 (footnote omitted). The Specification describes
improvements provided by the invention:
Embodiments advantageously improve upon existing
techniques and recruiting tools that rely upon binary metrics
that are limited to categorizing job applicants as either
successful or not. For example, in contrast to the non-binary
pCH metric disclosed herein, existing binary metrics cannot
show hiring gains resulting from increasing application volume
( e.g., within 0-25 additional applicants per job listing).
Traditional binary metrics also do not incorporate any applicant
quality signals or measurements, such as, for example, AQ
scores that contribute to pCH scores. The pCH metric described
herein also improves upon traditional binary metrics because
such binary metrics are inflexible across different types of jobs.
For example, unlike binary metrics, pCH scores are flexible
across different types of job applications (e.g., on-site
applications and off-site applications). Further, for example, in
contrast to binary metrics, pCH scores are flexible across
different organization sizes (e.g., small, medium, and large
companies that are seeking to fill positions).
Spec. ¶ 32.
The improvements described in the Specification are to the “metrics”
used in recruiting and showing hiring gains from increased applications.
These asserted improvements reside in the abstract ideas of the claim using
the AQ scores and the probability of a confirmed hire. The Specification
does not identify an “inventive” arrangement of the computer components
used to implement the steps of the claim. Like in SAP Am., Inc. v. InvestPic,
LLC, 898 F.3d 1161, 1167 (Fed. Cir. 2018), the “focus” of the claim “is on
selecting certain information, analyzing it using mathematical techniques,
and reporting or displaying the results of the analysis. That is all abstract. . . .
[C]laims focused on ‘collecting information, analyzing it, and displaying
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certain results of the collection and analysis’ are directed to an abstract
idea.”
Accordingly, we conclude that claim 1 is directed to an abstract idea.
Claims 14 and 20 recite the same method steps as claim 1 and are ineligible
under 35 U.S.C. § 101 for the same reasons. We leave it to the Examiner to
determine whether the dependent claims are also patent-ineligible.
The new grounds of rejection is as follows:
Claims 1, 14, and 20 are rejected as patent-ineligible under 35 U.S.C.
§ 101.

DECISION SUMMARY
In summary:
Claim(s)
Rejected
35
U.S.C.
§
Reference(s)/Basis Affirmed Reversed New
Ground
1–11,
14–20
103 Novack,
Obernikhin
1–11, 14–
20

12, 13 103 Novack,
Obernikhin,
Chevalier
12, 13
1, 14, 20 101 Eligibility 1, 14,
20
Overall
Outcome
1–20 1, 14,
20

TIME PERIOD FOR RESPONSE
This decision contains a new ground of rejection pursuant to
37 C.F.R. § 41.50(b). 37 C.F.R. § 41.50(b) provides “[a] new ground of
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rejection pursuant to this paragraph shall not be considered final for judicial
review.”
37 C.F.R. § 41.50(b) also provides that the Appellant, WITHIN TWO
MONTHS FROM THE DATE OF THE DECISION, must exercise one of
the following two options with respect to the new ground of rejection to
avoid termination of the appeal as to the rejected claims:
(1) Reopen prosecution. Submit an appropriate
amendment of the claims so rejected or new Evidence relating
to the claims so rejected, or both, and have the matter
reconsidered by the examiner, in which event the prosecution
will be remanded to the examiner. . . .
(2) Request rehearing. Request that the proceeding be
reheard under §41.52 by the Board upon the same Record. . . .

Further guidance on responding to a new ground of rejection can be
found in the Manual of Patent Examining Procedure § 1214.01 (9th Ed., Rev.
10.2019, June 2020).
No time period for taking any subsequent action in connection with
this appeal may be extended under 37 C.F.R. § 1.136(a). See 37 C.F.R.
§ 1.136(a)(1)(iv) (2019).
REVERSED; 37 C.F.R. 41.50(b)