Adobe Inc.

Patent Trials and Appeals Board

Feb 17, 2021

2020005656 (P.T.A.B. Feb. 17, 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.
14/996,806 01/15/2016 Piyush Gupta P5866-US 8306
108982 7590 02/17/2021
FIG. 1 Patents
116 W. Pacific Avenue
Suite 200
Spokane, WA 99201
EXAMINER
DAGNEW, SABA
ART UNIT PAPER NUMBER
3682
NOTIFICATION DATE DELIVERY MODE
02/17/2021 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):
Fig1Docket@fig1patents.com
PTOL-90A (Rev. 04/07)

UNITED STATES PATENT AND TRADEMARK OFFICE
____________

BEFORE THE PATENT TRIAL AND APPEAL BOARD
____________

Ex parte PIYUSH GUPTA,
NIKAASH PURI, MOHIT SRIVASTAVA, and
MANDAPAKA VENKAT JAGANNATH RAO

Appeal 2020-005656
Application 14/996,806
Technology Center 3600
____________

Before RICHARD M. LEBOVITZ, TAWEN CHANG, and
CYNTHIA M. HARDMAN, Administrative Patent Judges.

LEBOVITZ, Administrative Patent Judge.

DECISION ON APPEAL
Examiner rejected the claims under 35 U.S.C. § 101 as lacking patent
eligibility. 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 AFFIRM.

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 Adobe, Inc.
Appeal Br. 3.
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STATEMENT OF THE CASE
Examiner rejected claims 1–9 and 17–27 in the Final Office Action
(“Final Act.”) under 35 U.S.C. § 101 “because the claimed invention is
directed to an abstract idea without significantly more.” Final Act. 2.
There are three independent claims, claims 1, 17, and 21, each with a
set of dependent claims. Claims 1–9 are directed to a method; claims 17–20
are directed to a system; and claims 21–27 are directed to a computing
device. Appellant makes the same arguments for each set of claims. Appeal
Br. 32–35.2 We select claim 1 as representative to decide all issues in this
appeal. Claim 1 is reproduced below, with annotations added in brackets to
reference the limitations in the claim:
1. In a digital medium recommendation environment, a method
implemented by a computing device comprising:
[1] computing, by the computing device, [1a] user latent
factors from a user latent factor matrix representing a number of
users and a number of latent factors and [1b] item latent factors
from an item latent factor matrix representing a number of
items of digital content and the number of latent factors;
[2] forming, by the computing device, a plurality of
clusters based on similarity of the user latent factors to each
other;
[3] assigning, by the computing device, a plurality of
recommendations to respective clusters of the plurality of
clusters based on the user and item latent factors;
[4] obtaining, by the computing device subsequent to the
forming and the assigning, subsequent data that describes
interaction of a particular user of the number of users with a
respective item of the number of items of the digital content;
[5] updating, by the computing device, the user latent
factor of the number of user latent factors that corresponds to

2 Appellant’s summary of claim 21 in the Appeal Brief is not correct. Appeal
Br. 33. The limitations cited by Appellant in the summary of claim 21 do not
appear in the claims; we assume this is an error.
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the particular user using the subsequent data without updating a
user latent factor of the user latent factors that corresponds to
another user of the number of users;
[6] determining, by the computing device, which cluster
of the plurality of clusters corresponds to the updated user
latent factor based on similarity of the updated user latent factor
to user latent factors included within the plurality of clusters,
respectively;
[7] retrieving, by the computing device, a
recommendation from the plurality of recommendations
assigned to the determined cluster; and
[8] controlling, by the computing device, subsequent
interaction of the particular user with a respective item of the
digital content based on the recommendation.

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
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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 Mayo, 566 U.S. at
75–77).
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
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a drafting effort designed to monopolize the judicial exception.” 84 Fed.
Reg. 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
that is significantly more than the ineligible concept itself. 84 Fed. Reg. 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 method. A method is also a “process,” 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 examiners to search each limitation in the claim to
determine whether it recites a judicial exception. 84 Fed. Reg. 54.

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The first step of claim 1 is computing [1a] “user latent factors” from a
user latent factor matrix and [1b] “item latent factors” from an item latent
factor matrix. We interpret “latent factor” to mean a factor which underlies
the selection of a media item of a user or a characteristic of a media item, but
which is “not directly measurable”3 or is “not directly observable.”4
Clusters of user latent factors are formed in step 2 of the claim, based
on their similarity to each other. The Specification does not give examples of
user latent factors, but Zheleva refers to moods and listening preferences as
examples of latent characteristics, which we understand to be the same as
“factors.” Zheleva ¶¶ 23, 50. Thus, we understand that one example of
clustering of latent factors is clustering factors which reflect similar moods
or media preferences.
In step 3 of the claim, recommendations are assigned to the clusters
based on the user and item latent factors. A recommendation, as discussed in
the Specification, can be a recommendation of digital content, such as
advertisements and webpages. Spec. ¶ 23. As the Specification explains:
For example, a determination may be made that users are
similar, and then recommendations are made to a user based on
what similar users have liked. For instance, a user may like a
particular brand of phone based on interaction with a website.

3 Zheleva et al., US 2011/0314039 A1, published Dec. 22, 2011 (“Zheleva”),
¶ 23. Zheleva was cited as prior art by the Examiner in a rejection based on
35 U.S.C. § 103 that was subsequently withdrawn. Office Action (July 25,
2019) 5, 10.
4 Spec. ¶ 26: “From this, the user latent factors may be used to match item
latent factors such that features associated with a user match features
associated with an item in order to make recommendations that are not
directly observable from the matrix describing user interaction with items,
i.e., why the user chose to perform the interaction is not directly observable
but may be inferred using this technique.”
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Based on the interaction, which may include previous
interactions by the user, collaborative filtering techniques may
be used to first deduce that other users who liked that particular
brand of phone often end up purchasing another phone having
that brand. As a result, the website may recommend that
purchase through digital content relating to that brand, e.g., a
targeted advertisement, thereby predicting the user’s desires and
driving sales at the service provider 102.
Spec. ¶ 35.
In the subsequent steps of the claim, data that describes the
interactions of a user with digital content is obtained (step 4) and, using this
data, the user latent factor that corresponds to the user is updated without
updating the latent factor of other users (step 5). In step 6 of the claim, it is
determined what cluster, of the clusters identified in step 2, the updated
latent factor corresponds to. A recommendation is retrieved in step 7 from
the recommendations assigned to clusters in step 3, which saves computation
time by using recommendations that were already determined.
In the last step 8 of the claim, subsequent interactions of the user with
digital content is controlled by the recommendation retrieved in step 7. The
phrase “controlling . . . subsequent interactions” of a user with digital
content is not defined in the Specification. However, the Specification
explains that “user interactions” can be “clicking, viewing or purchasing
items” Spec. ¶ 38. Digital content can be webpages and advertisements, and
the corresponding interactions can be when “a user navigates through
webpages of a website, selects advertisements, and so forth.” Spec. ¶ 25. To
control the interaction, the digital content must be provided to the user in a
form in which it can be clicked on, viewed, etc., e.g., by displaying the
content to the user.

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Examiner found that the steps of the claim fall into the groupings of
“mathematical concepts” and “mental processes,” and involved “driving
sales at the service provider,” the latter which Examiner clarified in the
Answer as falling into the grouping of “certain methods of organizing
human activity,” listed in the Eligibility Guidance as an abstract idea. 2019
Eligibility Guidance, 84 Fed. Reg. at 51; Final Act. 3; Ans. 3–4 (stating that
step 8 of claim 1 of controlling the interaction of a user with digital content
is a business (misspelled as “bossiness”) arrangement).
Appellant stated that the claim “does not recite any method of
organizing human activity.” Appeal Br. 21. Appellant contends that
Examiner in the Answer “for the first time in prosecution” found that the
claims are directed to “Certain Methods of Organizing Human Activity” and
mischaracterized the claims in doing so. Reply Br. 3. Appellant argues that
the October PEG Update5 limits “Certain Methods of Organizing Human
Activity” to specific enumerated sub-categories and a “business
arrangement” is not one of them. Reply Br. 4.
Appellant’s arguments do not persuade us that Examiner erred.
Examiner specifically found in the Final Rejection that the claims in involve
“driving sales at the service provider.” Final Act. 3. The 2019 Eligibility
Guidance lists “commercial or legal interactions (including agreements in
the form of contracts; legal obligations; advertising, marketing or sales
activities or behaviors; business relations)” as falling in the grouping of
“Certain methods of organizing human activity.” 84 Fed. Reg. 52. Therefore,

5 Available at
https://www.uspto.gov/sites/default/files/documents/peg_oct_2019_update.p
df (last accessed Dec. 31, 2020) (“2019 PEG Update”).
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while the Examiner did not state that “driving sales” is a type of “sales
activities” and a specifically enumerated category of “certain methods of
organizing human activity,” it would have been understood to be within this
grouping of abstract ideas. Appellant in the Appeal Brief specifically
addressed this grouping, but did not challenge the Examiner’s finding that
the claims involved “targeted advertisement” and “driving sales.” Appeal Br.
21.
We agree with Examiner’s determination that claim 1 recites a method
of organizing human activity. The last step of claim 1 is “controlling” the
interaction of a user with digital content “based on the recommendation”
determined in the subsequent steps of the claim. The Specification discloses
that the recommendation can be a “targeted advertisement” for a specific
product that is predicted, based on the latent factors and clusters, to be a
product the user desires to purchase.6 The claim therefore is aimed at
promoting sales of certain products.
In addition to this, the choice of the advertisement is tailored to the
user based on the user’s latent factor, such a mood or media preference. As
discussed in Intellectual Ventures I LLC v. Capital One Bank (USA), 792
F.3d 1363, 1369 (Fed. Cir. 2015), “tailoring content based on the viewer’s

6 See Spec. ¶ 35 (copied supra 6–7); ¶ 36 (“For instance, it may also be
determined that users desiring that particular brand of phone often purchase
memory cards. Accordingly, for a new user looking at that brand of phone, a
recommendation may be made regarding the memory cards, which also
predict the user’s desires to drive sales and is thus beneficial to both the user
and the service provider 102.”)
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location or address” is “‘a fundamental . . . practice long prevalent in our
system . . .’” The court wrote:
There is no dispute that newspaper inserts had often been
tailored based on information known about the customer—for
example, a newspaper might advertise based on the customer’s
location. Providing this minimal tailoring—e.g., providing
different newspaper inserts based upon the location of the
individual—is an abstract idea.
Intellectual Ventures I, 729 F.3d at 1369 (emphasis added).
The claims on appeal tailor the choice of digital content based on a
user’s previous interactions with digital content (step 4 of claim 1). The
claim therefore customizes the digital content presented to the user based on
“information known about the customer,” and therefore, for same reasons as
in Intellectual Ventures I, the claim recites an abstract idea. Id.

Step 2A, Prong Two
Prong Two of Step 2A under the 2019 Eligibility Guidance asks
whether there are additional elements that integrate the exception into a
practical application. We must look at the claim elements individually and
“as an ordered combination” to determine whether the additional elements
integrate the recited abstract idea into a practical application. As explained
in the 2019 Eligibility Guidance, integration may be found when an
additional element “reflects an improvement in the functioning of a
computer, or an improvement to other technology or technical field” or
“applies or uses the judicial exception in some other meaningful way beyond
generally linking the use of the judicial exception to a particular
technological environment, such that the claim as a whole is more than a
drafting effort designed to monopolize the exception.” 84 Fed. Reg. at 55.
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The 2019 PEG Update further explains that “the specification should be
evaluated to determine if the disclosure provides sufficient details such that
one of ordinary skill in the art would recognize the claimed invention as
providing an improvement.” PEG Update 12.
The Specification states that “conventional digital content
recommendation techniques are resource and computationally expensive”
and therefore “are not performable in real time or involve compromises that
may have an effect on the accuracy of the recommendations and thus
decrease a likelihood of the recommendations being of interest to the users.”
Spec. ¶ 3. The Specification discloses that conventional approaches to
“achieve real time generation of recommendations . . . are not successful.”
Spec. ¶ 5. The approach described in the Specification addresses this
challenge. The Specification explains:
The recommendations are generated using the user latent
factors and the item latent factors for each of the plurality of
clusters using the cluster centroids. In this way, the number of
recommendations that are precomputed and stored may be
reduced, thus improving computational and storage efficiency.
Spec. ¶ 11.
Appellant, based on the disclosure in the Specification, states that the
claimed method “improves computer-related technology by providing
recitation of specific functionality regarding recommendation modelling and
computation techniques.” Appeal Br. 22. Appellant states that “the method
employs incremental matrix factorization and clustering, which may be used
to support real time generation of recommendations while addressing the
challenges of storage and computational resource consumption of
conventional techniques.” Id. Citing to the Specification, Appellant further
explains that the steps recited in the claim “support[] real time operation and
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thus increase[] a likelihood that the recommendation is accurate as
addressing a user’s current interaction with digital content that is not
possible in conventional techniques.” Id. at 26–27.
We have considered Appellant’s arguments, but find they do not
persuasively demonstrate error in Examiner’s rejection. The focus of the
claims, as explained by Appellant, is on applying “matrix factorization and
clustering” (see steps 1–3, 7 of claim 1) to obtain “real time generation of
recommendations.” Appeal Br. 22. The claims apply matrix factorization
and clustering (steps 1, 2), which are mathematical techniques, in the
“digital medium recommendation environment” (claim preamble), to obtain
recommendations (step 3) and then apply these recommendations to updated
latent factors associated with a user (steps 5, 7) to obtain faster and more
accurate recommendations. The recommendation is used to control the
subsequent interaction of the user with digital content (step 8), such as by
providing advertisements or webpages that the user can click on and view,
and purchase items. The rejected claims therefore analyze information about
a user’s preferences (“user latent factors”) using mathematical techniques
(matrix factorization and clustering) to obtain an updated recommendation
about digital content, and then provide the content to the user. The collection
and analysis of information is abstract. See SAP America, Inc. v. InvestPic,
LLC, 898 F.3d 1161, 1167 (Fed. Cir. 2018). The steps of updating the user
latent factor (steps 4, 5), determining a cluster to which it belongs (step 6),
retrieving the recommendation associated with the cluster (step 7), and then
directing the user to that recommendation (step 8) are “all abstract” and
nothing more than the necessary steps to perform the abstract idea of
promoting sales activities. See BOOM! PAYMENTS, Inc. v. Stripe, Inc., No.
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2020-1274, 2021 WL 116545, *4 (Fed. Cir. 2021) (nonprecedential) (“[W]e
agree with Stripe that these steps only explicate the necessary steps of an
escrow arrangement and do not change the direction of the claims.
Accordingly, we conclude that the claims are directed to an abstract idea at
step one.”).
Appellant argues that the claims are “analogous” to those in DDR
Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245 (Fed. Cir. 2014) because
the claims are “directed to addressing a digitally-rooted challenge that is
particular to the Internet.” Appeal Br. 24. Specifically, Appellant argues that
the “recommendation control techniques using incremental matrix
factorization and clustering” reduces “the number of recommendations that
are precomputed and stored . . . , thus improving computational and storage
efficiency.” Appeal Br. 27. Appellant argues that “claim 1 is rooted in
computer technology in order to overcome a problem specifically arising in
the realm of computer networks and massive amounts of data, which
represents a practical application amounting to significantly more than an
abstract idea.” Id. at 27–28.
An improvement in “computational and storage efficiency” as
asserted by Appellant is insufficient to impart eligibility on the claims. As
explained in Intellectual Ventures I LLC, 792 F.3d at 1370, “merely adding
computer functionality to increase the speed or efficiency of the process
does not confer patent eligibility on an otherwise abstract idea.” The asserted
improvement described in the claims does not involve an element which is
in addition to the steps necessary to make the recommendation of step 8 of
the claim, but rather is recited in the computations involving matrix
factorization, clustering, and generating recommendations “using the user
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latent factors and the item latent factors for each of the plurality of clusters
using the cluster centroids.” Reply Br. 5. These steps are part of the abstract
idea.
DDR is not analogous to the claims in this appeal. In DDR, 773 F.3d
at 1249–50, the claim comprised an “active link,” which when activated,
identifies the “source page” on which the link has been activated, retrieves
the source data from the source page, and “using the data retrieved,
automatically generate[s] and transmit[s] to the web browser a second web
page that displays: (A) information associated with the commerce object
associated with the link that has been activated, and (B) the plurality of
visually perceptible elements visually corresponding to the source page.”
The court found that the claims “address the problem of retaining website
visitors that, if adhering to the routine, conventional functioning of Internet
hyperlink protocol, would be instantly transported away from a host’s
website after ‘clicking’ on an advertisement and activating a hyperlink.” Id.
at 1257. The court found that the distinguishing feature of the claims was
that that they “specify how interactions with the Internet are manipulated to
yield a desired result—a result that overrides the routine and conventional
sequence of events ordinarily triggered by the click of a hyperlink.” Id. at
1258. Specifically, the claims in DDR recited a specific element that
provided a functionality to the claimed system and method, serving as the
basis for patent eligibility.
Here, Appellant has not persuasively identified an additional element
in the claim that is analogous to the “link” in DDR. As explained in the 2019
Eligibility Guidance, integration into a practical application may be found
when an additional element “reflects an improvement in the functioning of a
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computer, or an improvement to other technology or technical field.” 84
Fed. Reg. 55. The improvement asserted by Appellant is in using matrix
factorization and clustering to determine a recommendation, and then based
on an updated latent factor, retrieve one of the previously determined
recommendations (see steps 5–7 of claim 1). Based on the recommendation,
the subsequent interaction of the user with digital content is controlled, but
the claim does not describe how the interaction is controlled, and based on
the Specification as explained above, it can be providing a webpage or
advertisement which the user can navigate through or selection. Such
interaction is not restricted to a unique link with unique display as in DDR,
or provide an improved way of controlling the interaction of the user with
the recommended digital item.
To further support their argument, Appellant cited Example 40 of the
2019 Subject Matter Eligibility Examples (Jan. 7, 2019) (“2019 SMEE”).
Appellant states that “[s]imilar to how in the example claim the additional
elements limit data collection to avoid hindrance of network performance,
the additional elements in claim 1 recite a specific manner of forming a
plurality of clusters that provide a specific improvement over prior systems.”
Appeal Br. 29 (emphasis omitted). The analysis of Example 40 explained:
Although each of the collecting steps analyzed individually
may be viewed as mere pre- or post-solution activity, the claim
as a whole is directed to a particular improvement in collecting
traffic data. Specifically, the method limits collection of
additional Netflow protocol data to when the initially collected
data reflects an abnormal condition, which avoids excess traffic
volume on the network and hindrance of network performance.
The collected data can then be used to analyze the cause of the
abnormal condition. This provides a specific improvement over
prior systems, resulting in improved network monitoring. The
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claim as a whole integrates the mental process into a practical
application.
2019 SMEE 11.
Implicit in this analysis is the finding that the steps relied upon to
confer eligibility of the claim in Example 40 are not the mental process,
itself. For example, the explanation as to why the claim is eligible refers to
the last step of the claim of “collecting additional traffic data relating to the
network traffic when the collected traffic data is greater than the predefined
threshold, the additional traffic data comprising Netflow protocol data”
which is a data collection step. 2019 SMEE 10.
The claims here are distinguishable because the asserted improvement
and “additional elements” identified by Appellant (Appeal Br. 29) are the
specific steps in the claim that are necessary to carry out the abstract idea.
Appellant did not explain how the data collection in step 4 (“obtaining . . .
subsequent data”), the retrieving of recommendations assigned to the
clusters in step 7, and the controlling of interactions in step 8 provide the
improvement to the claimed method. To the contrary, Appellant attributes
the improvement to other steps in the claim which we found to be abstract:
In particular, by forming a plurality of clusters using the user
latent factors, such as to group users of the user latent factor
matrix based on similarity, one to another. In this way, the
number of recommendations that are precomputed and stored
may be reduced, thus improving computational and storage
efficiency.
Appeal Br. 29 (footnote citation to Specification and emphasis omitted).
The claim also does not describe a specific way in which the latent
factors and recommendations are computed and determined. As explained in
Dropbox, Inc. v. Synchronoss Technologies, Inc., 815 F. App’x 529, 534
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(Fed. Cir. 2020) (nonprecedential), it has been “consistently held that an
‘inventive concept’ exists when a claim ‘recite[s] a specific, discrete
implementation of the abstract idea’ where the ‘particular arrangement of
elements is a technical improvement over [the] prior art.” (quoting BASCOM
Glob. Internet Servs. v. AT&T Mobility LLC, 827 F.3d 1341, 1350 (Fed. Cir.
2016)). As additionally explained in Dropbox:
The patent has to describe how to solve the problem in a
manner that encompasses something more than the “principle in
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 F. App’x at 533 (additional citation omitted); see also McRO,
Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1315 (Fed. Cir. 2016)
(“[C]laimed process uses a combined order of specific rules that renders
information into a specific format that is then used and applied to create
desired results: a sequence of synchronized, animated characters.”).
While claim 1 recites a specific order of steps to identify a
recommendation, the steps individually are recited in a result-oriented way,
i.e., computing user and item latent factors (step 1), forming clusters (step
2), updating the latent factor (step 5), and determining which cluster of the
plurality of clusters corresponds to the updated user latent factor based on
similarity (step 6). The claim also does not teach how the interaction with
the digital content is accomplished (step 8).
Accordingly, for the foregoing reasons, we find that the recited
abstract idea is not integrated into a practical application.
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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.”
84 Fed. Reg. 56 (footnote omitted).
Appellant contends that the specific features recited in claim 1 are
patent-eligible because they are not well-understood, routine, or
conventional activity. Appeal Br. 30.
As explained above, the steps of “computing” latent factors (step 1),
forming clusters (step 2), assigning recommendations to clusters (step 3),
and determining to which cluster a latent factor belongs (step 6) are a part of
the abstract idea because they represent the specific steps necessary to
implement the abstract idea of promoting a sales activity. The steps are
performed on a generic computing device and do not recite a specific
implementation that would confer eligibility on the claim. The additional
steps in the claim involving the collection of data and the control of the
interaction with digital content display of the recommendation do not
provide an inventive step as asserted by Appellant.
It is true that “an inventive concept can be found in the non-
conventional and non-generic arrangement of known, conventional pieces.”
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BASCOM, 827 F.3d at 1350. As explained in Cellspin Soft, Inc. v. Fitbit,
Inc., 927 F.3d 1306, 1318 (Fed. Cir. 2019):
In BASCOM, we explained that the placement of a filtering tool
“at a specific location,” and configured in a particular way,
evidenced an inventive concept because the “limited record”
before us did not demonstrate that the “specific method of
filtering” claimed “ha[d] been conventional or generic.” Id. On
the limited record here, and at this stage in the case, we reach
the same result with respect to the elements recited by the
asserted claims. As noted above, Cellspin specifically alleged
that using HTTP at a specific location, here at the intermediary
mobile device, was inventive.
However, Cellspin specifically distinguished ineligible claims that
“did not ‘differentiate’ the claims from the underlying mental process.”
Cellspin, 927 F.3d at 1319. Rather, Cellspin found that on the record before
it the claims “recite a specific, plausibly inventive way of arranging devices
and using protocols.” Id. Here, it is not asserted that the additional elements
recited in the claim arrange devices and use protocols inventively. The sole
device in the claim is a generic computing device and there is no evidence
that it is arranged or being used in an inventive way. The protocol in
Cellspin comprised “establishing a paired connection between the Bluetooth
enabled data capture device and the Bluetooth enabled mobile device.” Id. at
1310 (emphasis omitted). The steps in claim 1 simply involve collecting
(steps 4, 5, 7) and analyzing data (steps 1, 2, 3, 6), and controlling an
interaction with digital content (step 8) based on the collection and analysis
steps, all of which are performed with a generic computing device.
Appellant did not establish the last step of the claim provided an
improvement to the recited method. Rather, it appears that such step is
accomplished conventionally, for example, by displaying a link, an
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advertisement, etc., that a user can interact with. We are not persuaded that
there is inventive arrangement in these steps or that the steps provide
anything more than the fundamental economic practices of tailoring
advertisements to a particular user and to promoting sales.
Appellant also argues that the step in claim 1 of “forming, by the
computing device, a plurality of clusters based on similarity of the user
latent factors to each other” is inventive. Appeal Br. 32. However, even
assuming this step is not part of the abstract idea, Appellant overlooks the
findings made in the Non-Final Action 9 (July 25, 2019), where Examiner
cited Zheleva for determining clusters based on latent factors.7
For the foregoing reasons, we affirm the rejection of claim 1 as
patent-ineligible. Appellant makes the same arguments for claims 17 and 21.
Appeal Br. 32–35. These claims are therefore patent-ineligible for the same
reasons as claim 1. Claims 2–9, 18–20, and 22–27 are not argued separately
and fall with claims 1, 17, and 21. 37 C.F.R. § 41.37(c)(1)(iv).

CONCLUSION
In summary:
Claims
Rejected
35 U.S.C.
§
Reference(s)/Basis Affirmed Reversed
1–9, 17–27 101 Eligibility 1–9, 17–27

7 Zheleva ¶ 58: “It is also assumed that there are latent characteristics C={c1,
. . . , cK} which explain co-occurrence patterns of media items that users
consume, and they provide (soft) clustering of the media items M.” Zheleva
¶ 81: “It can be observed that some latent characteristics comprise clusters of
genres resembling the groupings of genre in the taxonomy shown in FIG. 3.”
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TIME PERIOD
No time period for taking any subsequent action in connection with
this appeal may be extended under 37 C.F.R. § 1.136(a)(1)(iv).

AFFIRMED