Facebook, Inc.

Patent Trials and Appeals Board

Oct 12, 2021

2021001407 (P.T.A.B. Oct. 12, 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.
15/482,447 04/07/2017 Sagar Chordia 26295-34719/US 9483
87851 7590 10/12/2021
Facebook/Fenwick
Silicon Valley Center
801 California Street
Mountain View, CA 94041
EXAMINER
TOKARCZYK, CHRISTOPHER B
ART UNIT PAPER NUMBER
3622
NOTIFICATION DATE DELIVERY MODE
10/12/2021 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):
fwfacebookpatents@fenwick.com
ptoc@fenwick.com
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
____________

BEFORE THE PATENT TRIAL AND APPEAL BOARD
____________

Ex parte SAGAR CHORDIA, KAI REN, ADIITYA PAL,
AMAC HERDAGDELEN, and TIAN WANG
____________

Appeal 2021-001407
Application 15/482,447
Technology Center 3600
____________

Before JOSEPH A. FISCHETTI, NINA L. MEDLOCK, and
BRUCE T. WIEDER, Administrative Patent Judges.

MEDLOCK, Administrative Patent Judge.

DECISION ON APPEAL

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STATEMENT OF THE CASE
Appellant1 appeals under 35 U.S.C. § 134(a) from the Examiner’s
final rejection of claims 1–7, 10–17, and 20. We have jurisdiction under
35 U.S.C. § 6(b).
We AFFIRM.
CLAIMED INVENTION
The Specification states, “[t]his disclosure relates generally to online
systems, and in particular to targeting content based on inferred user
interests in an online system” (Spec. ¶ 1).
Claims 1 and 11 are the independent claims on appeal. Claim 1,
reproduced below with bracketed notations added, is illustrative of the
claimed subject matter:
1. A method comprising:
[(a)] identifying a plurality of users having a first user
profile in a primary online system and a second user profile in a
secondary online system, the second user profile including one
or more interests of the user;
[(b)] selecting a training group of users from the
identified plurality of users, each user of the training group of
users having a target interest as one of the one or more interests
included in the second user profile in the secondary online
system;

1 We use the term “Appellant” to refer to “applicant” as defined in 37 C.F.R.
§ 1.42. Our decision references Appellant’s Appeal Brief (“Appeal Br.,”
filed May 29, 2020) and Reply Brief (“Reply Br.,” filed December 21,
2020), and the Examiner’s Answer (“Ans.,” mailed October 26, 2020) and
Final Office Action (“Final Act.,” mailed December 2, 2019). We note that
the pages of Appellant’s Appeal Brief are not numbered; we refer to the title
page as page 1 and treat the pages that follow as though consecutively
numbered. Appellant identifies Facebook, Inc. as the real party in interest
(Appeal Br. 2).
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[(c)] training a machine learning model to determine
inclusion in the training group, the machine learning model
trained with first user profiles of the training group of users, and
wherein the machine learning model inputs a plurality of features
of a first user profile in the primary online system and outputs a
prediction of whether the first user profile is included in the
training group based on the input features; and
[(d)] identifying an expanded group of users in the
primary online system by applying the trained machine learning
model to other users of the primary online system, wherein the
expanded group of users is eligible for targeting of content
according to the target interest.
REJECTIONS
Claims 1–7, 10–17, and 20 are rejected under 35 U.S.C. § 101 as
directed to a judicial exception without significantly more.
Claims 1–7, 10–17, and 20 are rejected under 35 U.S.C. § 102(a)(1) as
anticipated by Rajan et al. (US 2014/0280549 A1, published Sept. 18, 2014)
(“Rajan”).
ANALYSIS
Patent-Ineligible Subject Matter
Appellant argues the pending claims as a group (Appeal Br. 4). We
select independent claim 1 as representative. The remaining claims stand or
fall with claim 1. See 37 C.F.R. § 41.37(c)(1)(iv).
Under 35 U.S.C. § 101, “[w]hoever 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.” 35 U.S.C.
§ 101. The Supreme Court, however, has long interpreted § 101 to include
an implicit exception: “[l]aws of nature, natural phenomena, and abstract
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ideas” are not patentable. Alice Corp. v. CLS Bank Int’l, 573 U.S. 208, 216
(2014).
The Supreme Court, in Alice, reiterated the two-step framework
previously set forth in Mayo Collaborative Services v. Prometheus
Laboratories, Inc., 566 U.S. 66 (2012), “for distinguishing patents that claim
laws of nature, natural phenomena, and abstract ideas from those that claim
patent-eligible applications of those concepts.” Alice Corp., 573 U.S. at 217.
The first step in that analysis is to “determine whether the claims at issue are
directed to one of those patent-ineligible concepts.” Id. If the claims are not
directed to a patent-ineligible concept, e.g., an abstract idea, the inquiry
ends. Otherwise, the inquiry proceeds to the second step where the elements
of the claims are considered “individually and ‘as an ordered combination’”
to determine whether there are additional elements that “‘transform the
nature of the claim’ into a patent-eligible application.” Id. (quoting Mayo,
566 U.S. at 79, 78). This is “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.’” Id. at 217–18 (alteration in original).
The U.S. Patent and Trademark Office (the “USPTO”) published
revised guidance on January 7, 2019, for use by USPTO personnel in
evaluating subject matter eligibility under 35 U.S.C. § 101. 2019 REVISED
PATENT SUBJECT MATTER ELIGIBILITY GUIDANCE, 84 Fed. Reg. 50 (Jan. 7,
2019) (the “2019 Revised Guidance”).2 That guidance revised the USPTO’s

2 The MANUAL OF PATENT EXAMINING PROCEDURE (“MPEP”) incorporates
the revised guidance and subsequent updates at Section 2106 (9th ed.
Rev. 10.2019, rev. June 2020).
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examination procedure with respect to the first step of the Mayo/Alice
framework by (1) “[p]roviding groupings of subject matter that [are]
considered an abstract idea”; and (2) clarifying that a claim is not “directed
to” a judicial exception if the judicial exception is integrated into a practical
application of that exception. Id. at 50.
The first step, as set forth in the 2019 Revised Guidance (i.e.,
Step 2A), is, thus, a two-prong test. In Step 2A, Prong One, we look to
whether the claim recites a judicial exception, e.g., one of the following
three groupings of abstract ideas: (1) mathematical concepts; (2) certain
methods of organizing human activity, e.g., fundamental economic
principles or practices, commercial or legal interactions; and (3) mental
processes. 2019 Revised Guidance, 84 Fed. Reg. at 54. If so, we next
determine, in Step 2A, Prong Two, whether the claim as a whole integrates
the recited judicial exception into a practical application, i.e., whether the
additional elements recited in the claim beyond the judicial exception, apply,
rely on, or use the judicial exception in a manner that imposes a meaningful
limit on the judicial exception, such that the claim is more than a drafting
effort designed to monopolize the judicial exception. Id. at 54–55. Only if
the claim (1) recites a judicial exception and (2) does not integrate that
exception into a practical application do we conclude that the claim is
“directed to” the judicial exception, e.g., an abstract idea. Id.
If the claim is determined to be directed to a judicial exception under
revised Step 2A, we next evaluate the additional elements, individually and
in combination, in Step 2B, to determine whether they provide an inventive
concept, i.e., whether the additional elements or combination of elements
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amounts to significantly more than the judicial exception itself; only then, is
the claim patent eligible. 2019 Revised Guidance, 84 Fed. Reg. at 56.
Here, in rejecting the pending claims under 35 U.S.C. § 101, the
Examiner determined that the claims, when given their broadest reasonable
interpretation, recite identifying a group of users eligible to receive targeted
content in accordance with a target interest, i.e., a method of organizing
human activity and, therefore, an abstract idea (Final Act. 4).3 The
Examiner also determined that the additional elements recited in the claims,
beyond the abstract idea, do not integrate the recited abstract idea into a
practical application (id. at 4–6), and that these additional elements are not
sufficient to amount to significantly more than the abstract idea itself (id.
at 6–7).
Step One of the Mayo/Alice Framework (2019 Revised Guidance, Step 2A)
We are not persuaded by Appellant’s argument that the Examiner
erred in determining that claim 1 is directed to an abstract idea (Appeal
Br. 4–11). The Federal Circuit has explained that “the ‘directed to’ inquiry
applies a stage-one filter to claims, considered in light of the specification,
based on whether ‘their character as a whole is directed to excluded subject
matter.’” Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335 (Fed. Cir.
2016) (quoting Internet Patents Corp. v. Active Network, Inc., 790 F.3d
1343, 1346 (Fed. Cir. 2015)). It asks whether the focus of the claims is on a

3 The Examiner determined that claims also recite a mental process and,
therefore, an abstract idea (Final Act. 4 (“‘[T]raining a machine learning
model’ can be as simple as devising a rule, e.g., ‘If the user likes socks, they
can be in the sock training group.” This step can reasonably be performed in
the human mind. Application of this rule can similarly be reasonably
performed in the human mind, as well as implemented on a computer.”)).
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specific improvement in relevant technology or on a process that itself
qualifies as an “abstract idea” for which computers are invoked merely as a
tool. See id. at 1335–36. Here, it is clear from the Specification (including
the claim language) that claim 1 focuses on an abstract idea, and not on an
improvement to technology and/or a technical field.
The Specification is titled “TARGETING CONTENT BASED ON
INFERRED USER INTERESTS,” and discloses, in the Background section,
that online systems, based on their increasing popularity, are able to collect
large amounts of information about users that they can then leverage to
provide their users with targeted content (Spec. ¶ 2). However, because
users vary in their engagement with online systems, more information may
be known for some users relative to other users — a situation that, according
to the Specification, “can result in some users receiving less relevant
targeted content (and missing out on the opportunity to receive more
relevant content)” (id.).
The claimed invention is ostensibly intended to address this problem
by providing a method for inferring the interests of those online system users
for whom little interest information is available, using other available
information, e.g., user characteristics, maintained by the online system. In
accordance with the claimed method, the online system, i.e., the primary
online system, first identifies users who have user profiles in both the
primary online system and another online system, i.e., the secondary online
system (Spec. ¶ 4). For a particular target interest, the primary online
system selects a training group of users, who have the target interest in their
user profile on the secondary online system, and applies machine learning
techniques to the training group users to generate an interest inference model
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that associates information in the training group users’ profiles in the
primary online system with the target interest (id.). The interest inference
model is applied to an input group of users who have user profiles in the
primary online system to identify a seed group of users for whom the target
interest can be inferred (id.). This seed group is then used to generate an
expanded group of users, via cluster-based expansion techniques, to whom
the primary online system can target content related to the target interest
(id.).
Consistent with this disclosure, claim 1 recites a method comprising:
(1) identifying users who have user profiles in both a primary online system
and a secondary online system, and selecting a training group of users who
have a target interest included in their user profiles on the secondary online
system, i.e.,
identifying a plurality of users having a first user profile in
a primary online system and a second user profile in a secondary
online system, the second user profile including one or more
interests of the user; [and]
selecting a training group of users from the identified
plurality of users, each user of the training group of users having
a target interest as one of the one or more interests included in
the second user profile in the secondary online system
(steps (a) and (b)); (2) training a machine learning model to determine
inclusion in the training group and, thereby, predict whether another user is
similar to the training group, i.e.,
training a machine learning model to determine inclusion
in the training group, the machine learning model trained with
first user profiles of the training group of users, and wherein the
machine learning model inputs a plurality of features of a first
user profile in the primary online system and outputs a prediction
of whether the first user profile is included in the training group
based on the input features
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(step (c)); and (3) applying the machine learning model to identify other
users of the primary online system to whom the system can target content
related to the target interest, i.e., “identifying an expanded group of users in
the primary online system by applying the trained machine learning model to
other users of the primary online system, wherein the expanded group of
users is eligible for targeting of content according to the target interest” (step
(d)).
Appellant argues that the rejection of claim 1 cannot be sustained at
least because claim 1 does not fall within the category of “[c]ertain methods
of organizing human activity” (Appeal Br. 7–10; see also Reply Br. 3–4).
Yet, Appellant cannot reasonably deny that leveraging knowledge about a
target interest of a subset of users of an online system to identify an
expanded group of users of the online system for targeting content, e.g.,
advertisements,4 related to the target interest constitutes “managing . . .
relationships or interactions between people” and/or commercial interactions
(including advertising, marketing or sales activities or behaviors)) under a
broad, but reasonable interpretation. This conclusion is, moreover, fully
consistent with Appellant’s Specification (see Ans. 8 (observing that
“Appellant’s specification describes at ¶¶ [0029]–[0031] how the marketing
information modeled and generated—i.e., identification of users in a group

4 See, e.g., Spec. ¶ 13 (A third party system 130 may . . . communicate
information to the primary online system 140, such as advertisements,
content, or information about an application provided by the third party
system 130.”)), ¶ 30 (“Content items eligible for presentation to the user
may include content items associated with bid amounts. The content
selection module 230 uses the bid amounts associated with ad requests when
selecting content for presentation to the user.”)).
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for receiving targeted content—is used to deliver targeted promotions or
advertising.”)). As such, we agree with the Examiner that claim 1 recites a
method of organizing human activity and, therefore, an abstract idea. See
2019 Revised Guidance, 84 Fed. Reg. at 52.
We also are not persuaded by Appellant’s argument that claim 1 is not
directed to an abstract idea because any alleged abstract idea is integrated
into a practical application (Appeal Br. 10–11; see also Reply Br. 4–6).
The 2019 Revised Guidance references MPEP, Ninth Edition
(rev. Jan 2018) (available at https://www.uspto.gov/web/offices/
pac/mpep/old/mpep_E9R08-2017.htm) § 2106.05(a)–(c) and (e) in
non-exhaustively listing considerations indicative that an additional element
or combination of elements may have integrated a recited judicial exception
into a practical application. 2019 Revised Guidance, 84 Fed. Reg. at 55.
In particular, the Guidance describes that an additional element may have
integrated the judicial exception into a practical application if, inter alia,
“[the] additional element reflects an improvement in the functioning of a
computer, or an improvement to other technology or technical field.” Id.
At the same time, the Guidance makes clear that merely including
instructions to implement an abstract idea on a computer, or merely using a
computer as a tool to perform an abstract idea; adding insignificant extra-
solution activity to the judicial exception; or only generally linking the use
of the judicial exception to a particular technological environment or field
are not sufficient to integrate the judicial exception into a practical
application. Id.
Appellant maintains here that a “technical problem arises in situations
where a primary online system’s content targeting capabilities are . . .
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limited to interests in user profiles on the primary online system” (Appeal
Br. 10–11) and that the claimed invention “embod[ies] an improvement
through the solution to the technical problem” (id. at 11). Appellant argues
that this solution (i.e., training a machine learning model with a training
group of users having corresponding profiles in the primary online system
and a secondary online system, wherein profiles in the secondary online
system include a target interest, and using the machine learning model to
determine an expanded group of users from the training group, significantly
increasing the content targeting capabilities of the primary online system) is
“embodied in the claim limitations, and thus the claimed invention integrates
any alleged abstract idea into a practical application” (id.). And Appellant
concludes, as such, “claim 1 can . . . be found eligible under Step 2A,
Prong 2” (id.).
Appellant’s argument is not persuasive at least because the relevant
question under Step 2A, Prong 2 is not whether the claimed invention itself
(i.e., generating and applying a machine learning model to identify an
expanded group of users of an online system to whom content can be
targeted) is a practical application; instead, the question is whether the claim
includes additional elements beyond the judicial exception that integrate the
judicial exception into a practical application. Here, the Examiner
determined, and we agree, that only additional elements recited in claim 1
beyond the abstract idea are generic computer components, i.e., “a primary
online system”; “a secondary online system”; and “a machine learning
model” (Final Act. 5 (citing Spec. ¶¶ 52–56)). “And after Alice, there can
remain no doubt: recitation of generic computer limitations does not make
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an otherwise ineligible claim patent-eligible.” DDR Holdings, LLC v.
Hotels.com, L.P., 773 F.3d 1245, 1256 (Fed. Cir. 2014).
We conclude, for the reasons outlined above, that claim 1 recites a
method of organizing human activity, i.e., an abstract idea, and that the
additional elements recited in the claim beyond the abstract idea are no more
than generic computer components used as tools to perform the recited
abstract idea. As such, they do not integrate the abstract idea into a practical
application. See Alice Corp., 573 U.S. at 223–24 (“[W]holly generic
computer implementation is not generally the sort of ‘additional featur[e]’
that provides any ‘practical assurance that the process is more than a drafting
effort designed to monopolize the [abstract idea] itself.’” (quoting Mayo,
566 U.S. at 77)). Accordingly, we agree with the Examiner that claim 1 is
directed to an abstract idea.
Step Two of the Mayo/Alice Framework (2019 Revised Guidance, Step 2B)
Having determined under step one of the Mayo/Alice framework that
claim 1 is directed to an abstract idea, we next consider under Step 2B of the
2019 Revised Guidance, the second step of the Mayo/Alice framework,
whether claim 1 includes additional elements or a combination of elements
that provides an “inventive concept,” i.e., whether an additional element or
combination of elements adds specific limitations beyond the judicial
exception that are not “well-understood, routine, conventional activity” in
the field (which is indicative that an inventive concept is present) or simply
appends well-understood, routine, conventional activities previously known
to the industry to the judicial exception. 2019 Revised Guidance,
84 Fed. Reg. at 56.
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We agree with the Examiner that claim 1 does not include additional
elements or a combination of elements that provides an inventive concept
(Final Act. 6–7). And Appellant offers no arguments to the contrary.
We are not persuaded, on the present record, that the Examiner erred
in rejecting independent claim 1 under 35 U.S.C. § 101. Therefore, we
sustain the Examiner’s rejection of claim 1, and claims 2–7, 10–17, and 20,
which fall with claim 1.
Anticipation
Independent Claim 1 and Dependent Claims 2–7 and 10
We are persuaded by Appellant’s argument that the Examiner erred in
rejecting claim 1 as anticipated by Rajan at least because Rajan does not
disclose or suggest “identifying a plurality of users having a first user profile
in a primary online system and a second user profile in a secondary online
system, the second user profile including one or more interests of the user,”
i.e., step (a), as recited in claim 1 (Appeal Br. 11–12).
Rajan is titled “Method and System for Efficient Matching of User
Profiles with Audience Segments,” and discloses that “[e]mbodiments of the
present teachings disclose [a] method, system, and programs that monetize
personalized user behavioral profiles by remapping the users to audience
segments related to advertisement[s]”; thus, “the users can be targeted with
advertisements that are personalized and hence are more likely to lead to
conversions” (Rajan, Abstr.; see also id. ¶ 91 (“By selecting and
personalizing advertising content and placing it into the content stream, the
present system maximizes user interaction with the advertising content.”)).
Rajan describes that, in one embodiment, a system and method directly
monetize user behavior by matching user profiles to audience segments (id.
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¶ 94), and that the method comprises (1) obtaining, a user profile
characterizing a user based on a first set of attributes; (2) mapping the first
set of attributes associated with the user profile to a second set of attributes
associated with an advertising audience segment; (3) estimating, based on
the mapping, an affinity between the user profile and the advertising
audience segment; (4) identifying, based on the affinity measure, advertising
content associated with the advertising audience segment; and (5) outputting
the advertising content (see, e.g., id. ¶¶ 13, 17, 101–105, claim 11).
In rejecting claim 1 as anticipated by Rajan, the Examiner cited
paragraphs 55, 80, 101, and 102 as disclosing the argued limitation (Final
Act. 8). In doing so, the Examiner equated the claimed “first user profile” to
Rajan’s audience segments and the claimed “second user profile” to Rajan’s
advertising segments (id.). The Examiner, thus, ostensibly interpreted
Rajan’s disclosure of “audience segments” and “advertising segments” in
paragraph 102 of Rajan as teaching two different user profiles on two
different online systems, e.g., a primary online system and a secondary
online system.
Rajan does not explicitly define the term “advertising segment”
(Appeal Br. 12). However, we agree with Appellant that it reasonably
appears from paragraph 102 of Rajan5 that “advertising segment refers to a

5 Paragraph 102 reads in part:
FIG. 15 depicts the steps taken during the advertisement segment
representation 1302 used to weight the advertisement in terms of the
audience segments. For each advertising segment, the system may first
obtain a set of keywords at step 1500 that represent[s] the commercial
interest of that segment. This set of keywords, for instance, may come
from the advertiser as in the case of Sponsored Search advertisements,
or in the case of Targeting or Look-a-like Modeling, given the segment
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leg (segment) of an advertising campaign” having an associated set of
keywords that represent the commercial interest of the advertising segment
(id.).6 We find nothing in the cited portion of Rajan that suggests that the
term instead equates to a user profile in an online system.
Rajan, likewise, does not explicitly define the term “audience
segment” (Appeal Br. 12). However, we agree with Appellant that the term
is reasonably understood, in light of the Rajan specification, to refer to a
“partition of users in the system defined by various parameters, wherein
Rajan’s objective is to categorize (or map) user profiles on the online system
into an audience segment for personalization of advertisement content” (id.;
see also e.g., Rajan ¶¶ 88 (describing that “[i]n an embodiment, methods and
system[s] relate to the placing of personalized advertisement content based
on the re-mapping or re-projecting of a . . . user’s profile . . . into an
advertisement audience segment for the placement of advertising content”);

of interest, human editors can provide a set that captures the
commercial intent of that segment. . . . . Next, the system needs to
remap the keywords and features identified for the ad segments in
step 1502 to the same feature space as that of the user behavioral
profiles and learn a weight factor in 1508 on each feature. . . . . At the
end of this process, there is a weighted vector computed at step 1508
for each segment, in which each component of the vector indicates the
importance of that feature in distinguishing the corresponding audience
segment [from other audience segments].
6 We understand Rajan to use the terms “advertisement segment” and
“advertising segment” (e.g., in paragraph 102) interchanageably. For
example, Rajan refers in paragraph 102 to “advertisement segment
representation 1302” (Rajan ¶ 102 (“FIG. 15 depicts the steps taken during
the advertisement segment representation 1302 used to weight the
advertisement in terms of the audience segments.”)). And, in Figure 13,
element 1302 is identified as “Advertising Segment representation 1302.”
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91 (“By re-projecting or remapping user behavioral profiles in a weighted
feature space and by expressing audience segments in the same feature
space, the similarity between the user behavioral profile and the audience
segments can be optimized to direct advertising to a targeted user base. Post
re-mapping, the user can be tagged as belonging to the set of audience
segments for which he/she has the maximum similarity to the targeted
audience.”)). We find no indication in the cited portion of Rajan that the
term “audience segment” connotes a user profile in an online system, as
called for in claim 1.
In view of the foregoing, we do not sustain the Examiner’s rejection
of claim 1 under 35 U.S.C. § 102(a)(1). For the same reasons, we also do
not sustain the Examiner’s rejection of dependent claims 2–7 and 10.
Independent Claim 11 and Dependent Claims 12–17 and 20
Independent claim 11 includes language substantially similar to the
language of claim 1, and stands rejected based on the same rationale applied
with respect to claim 1. We are persuaded, for the reasons set forth above,
that the Examiner erred in rejecting independent claim 1 under 35 U.S.C.
§ 102(a)(1). Therefore, we do not sustain the Examiner’s rejection, under
35 U.S.C. § 102(a)(1), of claims 11–17 and 20 for the same reasons.
CONCLUSION
In summary:
Claim(s)
Rejected
35 U.S.C. § Reference(s)/Basis Affirmed Reversed
1–7,
10–17, 20
101 Eligibility 1–7,
10–17, 20

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Claim(s)
Rejected
35 U.S.C. § Reference(s)/Basis Affirmed Reversed
1–7,
10–17, 20
102(a)(1) Rajan 1–7,
10–17, 20
Overall
Outcome
1–7,
10–17, 20

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).
AFFIRMED