Willard L. Simmons et al.

Patent Trials and Appeals Board

Oct 24, 2019

12856554 - (D) (P.T.A.B. Oct. 24, 2019)

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.
12/856,554 08/13/2010 Willard L. Simmons 18366.0012USU3 2360
23552 7590 10/24/2019
MERCHANT & GOULD P.C.
P.O. BOX 2903
MINNEAPOLIS, MN 55402-0903
EXAMINER
SITTNER, MICHAEL J
ART UNIT PAPER NUMBER
3622
NOTIFICATION DATE DELIVERY MODE
10/24/2019 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):
USPTO23552@merchantgould.com
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
____________________

BEFORE THE PATENT TRIAL AND APPEAL BOARD
____________________

Ex parte WILLARD L. SIMMONS and SANDRO N. CATANZARO
____________________

Appeal 2018-005918
Application 12/856,5541
Technology Center 3600
____________________

Before ERIC B. CHEN, HUNG H. BUI, and NABEEL U. KHAN,
Administrative Patent Judges.

BUI, Administrative Patent Judge.

DECISION ON APPEAL
Appellant seeks our review under 35 U.S.C. § 134(a) from the
Examiner’s Non-Final Rejection of claims 1–7 and 23–25, which are all the
claims pending in the application. Appeal Br. 31–33 (Claims App.). Claims
8–22 are canceled. Non-Final Act. 2. We have jurisdiction under 35 U.S.C.
§ 6(b).
We AFFIRM.2

1 We use the word “Appellant” to refer to “applicant(s)” as defined in
37 C.F.R. § 1.42. The real party in interest is DataXu, Inc. Appeal Br. 1.
2 Our Decision refers to Appellant’s Appeal Brief (“Appeal Br.”) filed
November 14, 2017; Examiner’s Answer (“Ans.”) mailed March 21, 2018;
Non-Final Office Action (“Non-Final Act.”) mailed June 14, 2017; and
original Specification (“Spec.”) filed August 13, 2010.
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STATEMENT OF THE CASE
Appellant’s invention relates to “presenting advertisements to digital
media users” and, specifically, relates to “methods and systems for applying
a plurality of algorithms to predict performance of online advertising
placements” based on a variety of market conditions, including, for example:
“advertiser data, historic event data, user data, real-time event data,
contextual data, and third-party commercial data.” Spec. ¶¶ 2–3, 5,
Abstract. According to Appellant, “historic event data” may include, for
example: “weather data, events data, local news data, or some other type of
data” such as “response rates to certain types of advertisements [that] may
be correlated to stock market movements.” Spec. ¶ 58. Real-time data may
include “information about the Internet Protocol (IP) address, context of an
ad and/or ad placement, a user’s history, geo-location information of the
user, social behavior, inferred demographics or some other type of data.”
Spec. ¶ 67. User’s behavior may include “an advertisement clickthrough
[clickrate], impression, webpage visit, transaction or purchase, or third party
data associated with the user.” Spec. ¶ 108.
Claim 1—the only independent claim—is illustrative of Appellant’s
invention, as reproduced below:
1. A computer implemented method for real-time
advertisement bidding in an ad exchange, the method
comprising:
using one or more processors:
applying a plurality of algorithms to predict performance
of online advertisement placements in an ad exchange;
tracking respective performance of each of the plurality of
algorithms under a variety of market conditions for each of the
advertisement placements, including analyzing an extent to
which each algorithm reflects actual economic performance;
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tracking current market conditions;
selecting an algorithm of the plurality of algorithms for
predicting performance of each of the respective advertisement
placements based on a comparison of relative performances of
the plurality of algorithms under the current market conditions;
and
automatically selecting and presenting to the ad exchange,
on behalf of an advertiser desirous of placing an advertisement,
a recommended bid amount for at least one of the advertisement
placements based on at least whether available funds exist in a
budget for the advertiser for the at least one of the advertisement
placements and on a predicted performance determined by the
selected algorithm for the at least one of the advertisement
placements.

Appeal Br. 31 (Claims App.).

EXAMINER’S REJECTIONS & REFERENCES
(1) Claims 1–7 and 23–25 stand rejected under 35 U.S.C. § 112(a)
or 35 U.S.C. § 112 (pre-AIA), first paragraph, as failing to comply with the
written description requirement. Non-Final Act. 4–7.
(2) Claims 1–7 and 23–25 stand rejected under 35 U.S.C. § 101
because the claimed invention is directed to a patent-ineligible “abstract
idea” without significantly more. Non-Final Act. 7–9.
(3) Claims 1–4 and 24–25 stand rejected under 35 U.S.C. § 103(a)
as being obvious over Galperin (US 8,571,930 B1; issued Oct. 29, 2013) and
Scholl et al. (US 8,447,651 B1; issued May 21, 2013; “Scholl”). Non-Final
Act. 10–17.
(4) Claims 5–7 and 23 stand rejected under 35 U.S.C. § 103(a) as
being obvious over Galperin, Scholl, and Henkin et al. (US 2010/0138271
A1; published June 3, 2010; “Henkin”). Non-Final Act. 17–21.
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DISCUSSION
I. 35 U.S.C. § 112(a)
In support of the § 112(a) rejection of claims 1–7 and 23–25, the
Examiner finds these claims fail to comply with the written description
requirement because “the invention is claimed and described in functional
language but the specification does not sufficiently identify how [] these
steps are performed,” i.e., “how the invention achieves the claimed
functions.” Non-Final Act. 4–6. For example, claim 1 recites, inter alia:
(1) “applying a plurality of algorithms to predict performance of online
advertisement placements in an ad exchange;” (2) “tracking respective
performance of each of the plurality of algorithms under a variety of market
conditions for each of the advertisement placements, including analyzing an
extent to which each algorithm reflects actual economic performance;” (3)
“tracking current market conditions;” and (4) “selecting an algorithm of the
plurality of algorithms for predicting performance of each of the respective
advertisement placements based on a comparison of relative performances of
the plurality of algorithms under the current market conditions.”
According to the Examiner, nowhere in the cited paragraphs 130, 160,
180, and 186 of Appellant’s Specification “are there actual algorithms for
‘predict[ing] performance of ad placements’; ‘analyzing the extent of
performance’; or how to ‘selecting algorithms based on comparisons’.”
Non-Final Act. 6.
We do not agree. The “written description” requirement is separate
and distinct from the “enablement” requirement under 35 U.S.C. § 112, first
paragraph. See Ariad Pharms., Inc. v. Eli Lilly & Co., 598 F.3d 1336, 1351
(Fed. Cir. 2010) (en banc). For example, to comply with the enablement
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requirement under 35 U.S.C. § 112, first paragraph, Appellant’s
Specification must adequately teach how to make and how to use a claimed
invention throughout its scope, without undue experimentation. Plant
Genetic Sys., N.V. v. DeKalb Genetics Corp., 315 F.3d 1335, 1339 (Fed. Cir.
2003). Naturally, the Specification must teach those of skill in the art “how
to make and how to use the invention as broadly as it is claimed.” In re
Vaeck, 947 F.2d 488, 496 (Fed. Cir. 1991).
In contrast to the enablement requirement, the written description
requirement under 35 U.S.C. § 112, first paragraph only requires Appellant
to “reasonably convey[] to those skilled in the art that the inventor had
possession of the claimed subject matter as of the filing date.” Ariad, 598
F.3d at 1351. “[T]he level of detail required to satisfy the written
description requirement varies depending on the nature and scope of the
claims and on the complexity and predictability of the relevant technology.”
Id. However, “the disclosure as originally filed does not have to provide in
haec verba support for the claimed subject matter at issue.” Purdue Pharma
L.P. v. Faulding Inc., 230 F.3d 1320, 1323 (Fed. Cir. 2000). In some cases,
“drawings alone may provide a ‘written description’ of an invention as
required by § 112.” Vas-Cath, Inc. v. Mahurkar, 935 F.2d 1555, 1565 (Fed.
Cir. 1991). Regardless, the disclosure must convey with reasonable clarity
to those skilled in the art that the inventor was in possession of the invention.
Id. at 1563–1564.
Here, Appellant has shown that there is sufficient structure and
description in the Specification as filed. For example, Figure 21 shows
verbatim support that the inventor had possession of the claimed (1)
“applying a plurality of algorithms to predict performance of online
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advertisement placements in an ad exchange;” (2) “tracking respective
performance of each of the plurality of algorithms under a variety of market
conditions . . . including analyzing an extent to which each algorithm reflects
actual economic performance;” (3) “tracking current market conditions;”
and (4) “selecting an algorithm of the plurality of algorithms for predicting
performance . . . based on a comparison of relative performances of the
plurality of algorithms under the current market conditions.” Spec. ¶ 174.
Likewise, Figures 1A–1B and 4 show Appellant’s real-time bidding system
100, including bidding machine facility 142 and learning machine facility
138 used to “select from an open list of multiple, competing algorithms” and
a plurality of valuation algorithms 140 used to select an advertisement.
Spec. ¶ 67, 71. According to Appellant, these algorithms are “machine
learning algorithms,” including, for example: “Naïve Bayes, Bayes Net,
Support Vector Machines, Logistic Regression, Neural Networks, and
Decision Trees.” Spec. ¶ 122. “[T]he learning machine facility 138 [shown
in Figures 1A–1B] may utilize various types of algorithms to refine the
economic valuation models of the real-time bidding machine facility 142”
and “may include, without any limitations, decision tree learning,
association rule learning, artificial neural networks, genetic programming,
inductive logic programming, support vector machines, clustering, Bayesian
networks, and reinforcement learning.” Spec. ¶ 163; see also Spec. ¶ 189.
Appellant has even acknowledged that these algorithms and “tools for
evaluating competing algorithms and models” are “known to a person of
ordinary skill in the art.” Spec. ¶¶ 127, 180, 186, 189–190.
Because Appellant has reasonably convey[ed] to those skilled in the
art that the inventor had possession of the claimed subject matter as of the
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filing date, we do not sustain the § 112(a) rejection of claims 1–7 and 23–25
for failure to comply with the “written description” requirement.

II. 35 U.S.C. § 101
In rejecting claims 1–7 and 23–25 under 35 U.S.C. § 101, the
Examiner determines these claims recite limitations that are analogous or
similar to concepts identified as abstract ideas by the court, such as: (1)
“collecting information, analyzing it, and displaying certain results of the
collection and analysis” as discussed in Electric Power Group, (2)
“collecting and comparing known information” as discussed in Classen, and
(3) mental processes and automation as discussed in Synopsis. Ans. 7–8
(citing Elec. Power Grp., LLC v. Alstom S.A., 830 F.3d 1350, 1354 (Fed.
Cir. 2016); Classen Immunotherapies, Inc. v. Biogen IDEC, 659 F.3d 1057
(Fed. Cir. 2011); and Synopsys v. Mentor Graphics, 839 F.3d 1138, 1146
(Fed. Cir. 2016) (holding that “analyzing information by steps people [can]
go through in their minds, or by mathematical algorithms, without more . . .
[are] mental processes within the abstract-idea category.”)).
The Examiner then determines additional elements (i.e., “one or more
processors” and “a plurality of algorithms”), when analyzed individually and
as an ordered combination, do not amount to significantly more than the
abstract idea because these additional elements (1) “are used merely to
generally link the use of the judicial exception to a particular technological
environment”; and (2) “are merely insignificant extra-solution activity.”
Non-Final Act. 7–8.
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Legal Framework
To determine whether claims are patent eligible under § 101, we apply
the Supreme Court’s two-step framework articulated in Alice Corp. v. CLS
Bank Int’l, 573 U.S. 208 (2014). First, we determine whether the claims are
directed to a patent-ineligible concept: laws of nature, natural phenomena,
and abstract ideas. Id. at 216. If so, we then proceed to the second step to
consider the elements of the claims “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. at
217. In other words, the second step is to “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 218 (alteration in original,
internal quotation marks omitted).
The Federal Circuit has described the Alice step-one inquiry as
looking at the “focus” of the claims, their “character as a whole,” and the
Alice step-two inquiry as looking more precisely at what the claim elements
add—whether they identify an “inventive concept” in the application of the
ineligible matter to which the claim is directed. See Elec. Power Grp., LLC
v. Alstom S.A., 830 F.3d 1350, 1353 (Fed. Cir. 2016); Enfish, LLC v.
Microsoft Corp., 822 F.3d 1327, 1335–36 (Fed. Cir. 2016); Internet Patents
Corp. v. Active Network, Inc., 790 F.3d 1343, 1346 (Fed. Cir. 2015).
In an effort to achieve clarity and consistency in how the U.S. Patent
and Trademark Office (the “Office”) applies the Supreme Court’s two-step
framework, the Office has published revised guidance interpreting governing
case law and establishing a prosecution framework for all patent-eligibility
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analysis under Alice and § 101 effective as of January 7, 2019. 2019
Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50–57
(Jan. 7, 2019) (“2019 Revised Guidance”).
2019 Revised Guidance
Under the 2019 Revised Guidance, we first look under Alice step 1 or
“Step 2A” to whether the claim recites:
(1) Prong One: any judicial exceptions, including certain
groupings of abstract ideas (i.e., [i] mathematical concepts,
[ii] mental processes—concepts performed in the human
mind (including an observation, evaluation, judgment,
opinion), or [iii] certain methods of organizing human activity
such as a fundamental economic practice or managing
personal behavior or relationships or interactions between
people); and

(2) Prong Two: additional elements that integrate the judicial
exception into a practical application (see Manual of Patent
Examining Procedure (“MPEP”) §§ 2106.05(a)–(c), (e)–
(h)).3
See 2019 Revised Guidance, 84 Fed. Reg. at 51–52, 55, Revised Step 2A,
Prong One (Abstract Idea) and Prong Two (Integration into A Practical
Application). Only if a claim: (1) recites a judicial exception, and (2) does
not integrate that exception into a practical application, do we then evaluate
whether the claim provides an “inventive concept” under Alice step 2 or
“Step 2B.” See 2019 Revised Guidance at 56; Alice, 573 U.S. at 217–18.
For example, we look to whether the claim:
1) adds a specific limitation beyond the judicial exception that is
not “well-understood, routine, conventional” in the field (see
MPEP § 2106.05(d)); or

3 All references to the MPEP are to the Ninth Edition, Revision 08.2017
(rev. Jan. 2018).
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2) simply appends well-understood, routine, and conventional
activities previously known to the industry, specified at a high
level of generality, to the judicial exception.
See 2019 Revised Guidance, 84 Fed. Reg. at 56.
In the briefing, Appellant and Examiner refer to prior USPTO
guidance regarding § 101, including, for example: 2014 Interim Guidance
on Patent Subject Matter Eligibility, 79 Fed. Reg. 74,618 (“the 2014 Interim
Guidance”). Non-Final Act. 9; Appeal Br. 12. However, the 2014 Interim
Guidance as well as other guidance, including: (1) July 2015 Update on
Subject Matter Eligibility, 80 Fed. Reg. 45,429 (July 30, 2015) (“the 2015
Update”); (2) May 2016 Subject Matter Eligibility Update, 81 Fed. Reg.
27,381 (May 6, 2016); and (3) Memorandum on Subject Matter Eligibility
Decisions dated Nov. 2, 2016, have been superseded by the 2019 Revised
Guidance. See 2019 Revised Guidance, 84 Fed. Reg. at 52. As such, our
analysis will not address the sufficiency of the Examiner’s rejection against
the cited prior guidance. Rather, our analysis will comport with the 2019
Revised Guidance, and we will review patent eligibility under § 101 de novo
as discussed below. Dealertrack, Inc. v. Huber, 674 F.3d 1315, 1333 (Fed.
Cir. 2012).
Alice/Mayo—Step 1 (Abstract Idea)
Step 2A–Prongs 1 and 2 identified in the Revised Guidance
Step 2A—Prong 1
Appellant argues (1) the Examiner mischaracterizes the claims
because “almost any patent [if looked] from far enough away, it could
arguably claim an abstract idea,” for example: “Alexander Graham Bell’s
patent could be said to claim the abstract idea of oral communication”; and
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(2) “the pending claims can be distinguishable over each of Classen, Electric
Power Group, and Synops[y]s” for several reasons, including:
(i) “Appellant[’s] claim 1 recites a specific, tangible application of
[] tracked information” and such information is not “known
information” that is collected and compared in Classen;

(ii) “Claim 1 recites a concrete solution to that problem [how to
predict performance of ad placements in real-time so that a bid
amount can be recommended to an ad exchange]—a) a plurality
of algorithms are applied to predict the performance of online ad
placements, b) the performance of the algorithms is tracked
under a variety of market conditions for each of the
advertisement placements, c) current market conditions are also
tracked, and d) an algorithm from the plurality is then selected
based on a comparison of relative performances of the plurality
of algorithms under the current market conditions” and such
steps are different from Electric Power Group; and

(iii) “the present claims specifically recite that a plurality of
algorithms are applied to predict the performance of online ad
placements, which is tracked under a variety of market
conditions for each of the advertisement placements” and such a
process cannot be performed mentally with pencil and paper.

Appeal Br. 12–18 (emphasis omitted).
We are persuaded by Appellant’s arguments only in part. Under the
“mental processes” doctrine, a patent claim that can be performed solely in a
person’s mind is considered an “abstract idea” and, as such, is patent-
ineligible under § 101. For example, in Gottschalk v. Benson, 409 U.S. 63,
64 (1972), the Supreme Court held a number-conversion method using a
mathematical algorithm is patent-ineligible under § 101 because the
conversion “can be done mentally” and “without a computer.” See Benson,
409 U.S. at 67. These “mental processes—or processes of human
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thinking—standing alone are not patentable even if they have practical
application.” In re Comiskey, 554 F.3d 967, 979 (Fed. Cir. 2009).
Similarly, in CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366,
1372 (Fed. Cir. 2011), the Federal Circuit held CyberSource’s method claim
for detecting fraud in credit card transactions conducted over the Internet
between consumer and merchant is drawn to an unpatentable “mental
process” because “[a]ll of [its] method steps can be performed in the human
mind, or by a human using a pen and paper” and do not require a computer.
However, the Federal Circuit also held that method claims “for calculating
an absolute position of a GPS receiver and an absolute time of reception of
satellite signals” are patent-eligible under § 101 because “the methods []
could not be performed without the use of a GPS receiver.” SiRF Tech., Inc.
v. Int’l Trade Comm’n, 601 F.3d 1319, 1331–32 (Fed. Cir. 2010).
As is commonly known to those skilled in the art, an algorithm is “a
finite sequence of steps for solving a logical or mathematical problem or
performing a task.” Microsoft Computer Dictionary 23 (5th ed. 2002). Such
an algorithm may be expressed in any understandable terms including as a
mathematical formula, in prose, in a flow chart, or “in any other manner that
provides sufficient structure.” Finisar Corp. v. DirecTV Group, Inc., 523
F.3d 1323, 1340 (Fed. Cir. 2008). According to Appellant, these
“algorithms may include, without any limitations, decision tree learning,
association rule learning, artificial neural networks, genetic programming,
inductive logic programming, support vector machines, clustering, Bayesian
networks, and reinforcement learning.” Spec. ¶¶ 122, 163.
Contrary to the Examiner’s characterization, we do not discern how “a
plurality of algorithms” recited in Appellant’s claim 1 can be performed
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solely in a person’s mind, especially when each of these algorithms is
tracked differently under a variety of market conditions to reflect actual
economic performance and a particular algorithm is selected among these
algorithms based on a comparison of relative performances of these
algorithms under the current market conditions.
We note, however, Appellant has acknowledged these algorithms and
“tools for evaluating competing algorithms and models” are “known to a
person of ordinary skill in the art” (Spec. ¶¶ 127, 180, 186, 189–190) and are
only used in the context of Appellant’s “presenting advertisements to digital
media users.” In particular, Appellant’s Specification and claim describe
“methods and systems for applying a plurality of algorithms to predict
performance of online advertising placements” based on a variety of market
conditions, including, for example: “advertiser data, historic event data, user
data, real-time event data, contextual data, and third-party commercial data.”
Spec. ¶¶ 2–3, 5, Abstract. For example, Appellant’s claim 1 recites a
“computer implemented method for real-time advertisement bidding in an ad
exchange” equipped with “one or more processors” for:
[1] applying a plurality of algorithms to predict performance
of online advertisement placements in an ad exchange;

[2] tracking respective performance of each of the plurality of
algorithms under a variety of market conditions for each of the
advertisement placements, including analyzing an extent to
which each algorithm reflects actual economic performance;

[3] tracking current market conditions;

[4] selecting an algorithm of the plurality of algorithms for
predicting performance of each of the respective advertisement
placements based on a comparison of relative performances of
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the plurality of algorithms under the current market conditions;
and

[5] automatically selecting and presenting to the ad exchange,
on behalf of an advertiser desirous of placing an advertisement,
a recommended bid amount for at least one of the advertisement
placements based on at least whether available funds exist in a
budget for the advertiser for the at least one of the advertisement
placements and on a predicted performance determined by the
selected algorithm for the at least one of the advertisement
placements.

Appeal Br. 31 (Claims App.) (bracketing added).
These limitations of Appellant’s claim 1, under their broadest
reasonable interpretation, recite a method of bidding an advertisement in an
ad exchange of an advertising agency by way of an algorithm selected from
a plurality of algorithms to predict performance of online advertisement
placements in an ad exchange, which is a known promotional and financial
activity and a fundamental economic practice in our system of commerce.
Spec. ¶¶ 2–5; Figures 1A–1B, 13.
Such activities are squarely within the realm of abstract ideas, like
(1) the risk hedging in Bilski v. Kappos, 561 U.S. 593 (2010); (2) the
intermediated settlement in Alice, 573 U.S. at 220; (3) verifying credit card
transactions in CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366,
1370 (Fed. Cir. 2011); (4) guaranteeing transactions in buySAFE, Inc. v.
Google, Inc., 765 F.3d 1350, 1354 (Fed. Cir. 2014); (5) distributing products
over the Internet in Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709 (Fed. Cir.
2014); (6) determining a price of a product offered to a purchasing
organization in Versata Dev. Grp., Inc. v. SAP Am., Inc., 793 F.3d 1306
(Fed. Cir. 2015); and (7) pricing a product for sale in OIP Techs., Inc. v.
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Amazon.com, Inc., 788 F.3d 1359 (Fed. Cir. 2015). Bidding for an
advertisement in an ad exchange regardless of how that advertisement is
selected and placed, whether in person or online, is a basic building block of
a market economy and, like risk hedging and intermediated settlement, is an
“abstract idea” beyond the scope of § 101. See Alice, 573 U.S. at 220.
We, therefore, conclude limitations (1)–(5) in Appellant’s claim 1
recite nothing more than bidding for an advertisement placement in an ad
exchange, which is “a fundamental economic practice” as identified in the
Revised Guidance, and, thus, an abstract idea. See 2019 Revised Guidance
(Revised Step 2A, Prong One), 84 Fed. Reg. at 52, 54.
Step 2A—Prong 2 (Integration into Practical Application)
Under Revised Step 2A, Prong Two of the Revised Guidance, we must
determine if the claims (i.e., additional limitations beyond the judicial
exception) integrate the judicial exception into a practical application.
However, we discern no additional element (or combination of elements)
recited in Appellant’s claim 1 and its dependent claims 2–7 and 23–25 that
integrates the judicial exception into a practical application. See Revised
Guidance, 84 Fed. Reg. at 54–55 (“Prong Two”).
For example, Appellant’s additional elements (i.e., processor and “a
plurality of algorithms”) recited in claim 1 do not (1) improve the
functioning of a computer or other technology, (2) are not applied with any
particular machine (except for generic computer components), (3) do not
effect a transformation of a particular article to a different state, and (4) are
not applied in any meaningful way beyond generally linking the use of the
judicial exception to a particular technological environment, such that the
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claim as a whole is more than a drafting effort designed to monopolize the
exception. See MPEP §§ 2106.05(a)–(c), (e)–(h).
Appellant argues “claim 1 recites a method in which a plurality of
predictive algorithms is used in an online advertisement system, to predict
the performance of online advertisement placements” and provide “[a
solution that is] necessarily rooted in computer technology” because (1) the
claim relates to “a specialized computing system [as shown in Figure 1A]”
using “a plurality of predictive algorithms” and (2) “the solution is used ‘in
order to overcome a problem specifically arising in the realm of computer
networks’” similar to the claims in DDR Holdings, LLC v. Hotels.com, L.P.,
773 F.3d 1245, 1257 (Fed. Cir. 2014). Appeal Br. 18–19. In addition,
Appellant also argues “the present claims provide a significant improvement
to technologies or computers themselves” and “provide[] a transformation of
data (from market conditions to predicted performance to a recommended
bid amount in an online ad exchange)” which meets the “machine or
transformation [MoT]” test. Appeal Br. 19–20.
We do not agree. First, as recognized by the Federal Circuit in
Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 716 (Fed. Cir. 2014), Bilski’s
“machine-or-transformation” (MoT) test can provide a “‘useful clue’” in the
second step of the Alice framework. See In re Bilski,4 545 F.3d 943, 954

4 In In re Bilski, the Federal Circuit adopted a “machine-or-transformation”
(MoT) test to determine whether a process claim is eligible under 35 U.S.C.
§ 101. However, the Supreme Court held, in Bilski v. Kappos, 561 U.S. 593,
604 (2010), that the “MoT” test, while a “useful and important clue,” is no
longer the sole test for determining the patent-eligibility of process claims
under § 101. Since Bilski v. Kappos, the Supreme Court has created a two-
step framework in Alice, 573 U.S. at 215 to address whether a claim falls
outside of § 101, which we discuss infra.
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(Fed. Cir. 2008) (en banc). Under Bilski’s MoT test, a claimed process can
be considered patent-eligible under § 101 if: (1) “it is tied to a particular
machine or apparatus”; or (2) “it transforms a particular article into a
different state or thing.” Bilski, 545 F.3d at 954 (citing Gottschalk, 409 U.S.
at 70, 93 S. Ct. 253). However, Appellant’s predicting performance of
online advertisement placements in an ad exchange recited in claim 1 is
neither sufficiently “tied to a particular machine or apparatus” nor involved
in any type of transformation of any particular article.5
Second, we note Appellant’s claims 1–7 and 23–25 are neither deeply
rooted in computer technology as outlined in DDR Holdings, LLC v.
Hotels.com, L.P., 773 F.3d 1245 (Fed. Cir. 2014), nor do they seek to
improve any type of computer capabilities, such as a “self-referential table
for a computer database” outlined in Enfish, LLC v. Microsoft Corp., 822
F.3d 1327, 1336–37 (Fed. Cir. 2016). As recognized by the Examiner,
“‘applying undisclosed plurality of algorithms’ does not provide a
practitioner with a ‘concrete solution’ for ultimately practicing the steps of
predicting ad placement performance . . . which are necessary for
automatically selecting and presenting to the ad exchange a recommended
bid.” Ans. 6. There is no support from Appellant’s Specification for any
feature of the so-called “plurality of algorithms” that would improve any
existing computer technology or would overcome any problem arising in the
realm of computer networks, as Appellant argues. Appeal Br. 18–19.
Instead, Appellant’s claims seek to utilize generic processors as a tool to

5 Alice also confirmed that if a patent’s systems claims are no different in
substance from its method claims, they will rise and fall together. 573 U.S.
at 226. The same is true of the Alice patent’s media claims. Id.
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perform the recited abstract idea. Likewise, Appellant’s claims utilize “a
plurality of algorithms” and “tools for evaluating competing algorithms and
models,” albeit “known to a person of ordinary skill in the art” as
acknowledged by Appellant’s Specification (Spec. ¶¶ 127–129, 180, 186,
189–190) but “undisclosed” as characterized by the Examiner (Ans. 6), to
predict performance of online advertising placements. Spec. ¶ 5.
Contrary to Appellant’s argument, using these known, but
“undisclosed” algorithms to predict performance of online advertising
placements recited in claim 1, does not provide any “technical solution to a
technical problem” as contemplated by the Federal Circuit in DDR (see
MPEP § 2106.05(a)), and is insufficient to show “integration into a practical
application.” See MPEP § 2106.05(f). Instead, these generic computer
components are simply the “automation of the fundamental economic
concept.” OIP Techs., 788 F.3d at 1362–63. “[M]erely requir[ing] generic
computer implementation,” “does not move into [§] 101 eligibility territory.”
buySAFE, 765 F.3d at 1354 (second alteration in original).
A claim for a new abstract idea is still an abstract idea. See Synopsys,
Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1151 (Fed. Cir. 2016). “No
matter how much of an advance in the finance field the claims recite, the
advance lies entirely in the realm of abstract ideas, with no plausibly alleged
innovation in the non-abstract application realm.” See SAP Am., Inc. v.
InvestPic, LLC, 898 F.3d 1161, 1163 (Fed. Cir. 2018).
For these reasons, we are not persuaded that Appellant’s “additional
elements” recited in claims 1–7 and 23–25 integrate the abstract idea into a
practical application.
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Alice/Mayo—Step 2 (Inventive Concept)
Step 2B identified in the Revised Guidance
Under the 2019 Revised Guidance, only if a claim: (1) recites a
judicial exception, and (2) does not integrate that exception into a practical
application, do we then look to whether the claim adds a specific limitation
beyond the judicial exception that is not “well-understood, routine,
conventional” in the field (see MPEP § 2106.05(d)); or, simply appends
well-understood, routine, conventional activities previously known to the
industry, specified at a high level of generality, to the judicial exception.
See 2019 Revised Guidance, 84 Fed. Reg. at 56. However, we find no
element or combination of elements recited in Appellant’s claims 1–7 and
23–25 that contain any “inventive concept” or add anything “significantly
more” to transform the abstract concept into a patent-eligible application.
Alice, 573 U.S. 208 at 221.
Appellant does not identify any specific limitation of claim 1 beyond
the judicial exception that is not “‘well-understood, routine, conventional’
activity in the field” as per MPEP § 2106.05(d). Instead, Appellant argues
“the claimed technique . . . facilitates the ability to predict performance of a
variety of advertisement placements” and then “automatically selects and
presents to an ad exchange, a recommended bid amount for at least one of
the advertisement placements” and, as such, “the claim[ed] elements do not
amount to ‘merely insignificant extra-solution activity.’” Appeal Br. 20–21.
We do not agree. As previously discussed, utilizing generic computer
components (e.g., processors and “algorithms”) does not alone transform an
otherwise abstract idea into patent-eligible subject matter. As our reviewing
court has observed, “after Alice, there can remain no doubt: recitation of
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generic computer limitations does not make an otherwise ineligible claim
patent-eligible.” DDR, 773 F.3d at 1256 (citing Alice, 573 U.S. at 222).
Preemption
Lastly, Appellant argues the claims do not seek to “tie up or pre-empt
others from using any presumed abstract idea” but does not explain why.
Appeal Br. 21.
We do not agree. The lack of preemption is a necessary clue for
patent eligibility, but it is not sufficient for patent eligibility. As the McRO
court explicitly recognized, “the absence of complete preemption does not
demonstrate patent eligibility.” See McRO, Inc. v. Bandai Namco Games
Am. Inc., 837 F.3d 1299, 1315 (Fed. Cir. 2016) (quoting Ariosa Diagnostics,
Inc. v. Sequenom, Inc., 788 F.3d 1371, 1379 (Fed. Cir. 2015)). Furthermore,
“[w]here a patent’s claims are deemed only to disclose patent ineligible
subject matter” under the Alice/Mayo framework, “preemption concerns are
fully addressed and made moot.” Ariosa, 788 F.3d at 1379.
Because Appellant’s independent claim 1 is directed to a patent-
ineligible abstract concept and does not recite an “inventive concept” or
provide a solution to a technical problem under the second step of the Alice
analysis, we sustain the Examiner’s § 101 rejection of independent claim 1
and its dependent claims 2–7 and 23–25 not separately argued.

III. 35 U.S.C. § 103(a)
In support of the § 103(a) rejection of claims 1–4, 24, and 25, the
Examiner finds Galperin and Scholl teaches all limitations of Appellant’s
invention. For example, the Examiner finds Galperin teaches most aspects
of Appellant’s invention, including: (1) “applying a plurality of algorithms
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to predict performance of online advertisement placements in an ad
exchange;” (2) “tracking respective performance of each of the plurality of
algorithms under a variety of market conditions . . .” (3) “tracking current
market conditions;” (4) “selecting an algorithm of the plurality of algorithms
. . . based on a comparison of relative performances of the plurality of
algorithms under the current market conditions.” Non-Final Act. 10–12
(citing Galperin 25:15–30, 33:15–25, Fig. 7).
To support the conclusion of obviousness, the Examiner relies on
Scholl for teaching the last step of claim 1’s “automatically selecting and
presenting to the ad exchange . . . a recommended bid amount for at least
one of the advertisement placements based on at least [1] whether available
funds exist in a budget . . . [2] a predicted performance determined by the
selected algorithm for the at least one of the advertisement placements.”
Non-Final Act. 12–13 (citing Scholl 7:1–32, 8:55–60).
Appellant acknowledges Galperin teaches “strategies for conducting
an advertisement campaign using a cost-per-transaction (CPT) pricing model
in which an advertiser is charged when an end-user takes some express
action in response to viewing the ad,” including (1) “computing an expected
value, ranking the ad with respect to other ads, pricing the ad, and tracking
performance” and (2) “compar[ing] the performance of different [cost-per-
transaction (CPT)] models in parallel, particularly for click-through rate
(CTR), and [] select[ing] the model that appears to be doing the best job at
modeling the performance of the ad.” Appeal Br. 23–24 (citing Galperin
6:64–7:2, 25:15–28).
However, Appellant argues: (1) “there is no disclosure or suggestion
anywhere in this reference that each of these models can or should be
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tracked under a variety of market conditions and for each of the ad
placements, as specifically recited in present claim 1” and (2) “there is no
teaching that current market conditions can or should be tracked, and
likewise, that an algorithm is selected based on a comparison of
relative performances of the plurality of algorithms under the current
market conditions.” Appeal Br. 24.
Appellant also argues “Scholl cannot overcome these deficiencies of
Galperin” because (1) “Scholl does not teach an ad exchange and, therefore
cannot disclose ‘selecting and presenting to an ad exchange’” as recited in
claim 1; (2) “Scholl only teaches a search engine determining whether or not
to accept a bid” and not “selecting . . . a recommended bid amount” as
recited in claim 1; and (3) “Scholl still does not disclose selecting one of the
factors based on a comparison of relative performances of the factors.”
Appeal Br. 25–27 (citing Scholl 3:6–18).
Appellant’s arguments are not persuasive. Instead, we find the
Examiner has provided a comprehensive response to Appellant’s arguments
supported by evidence. Ans. 7–9. As such, we adopt the Examiner’s
findings and explanations provided therein, as discussed below. Id. For
additional emphasis, we note claim terms are given their broadest reasonable
interpretation consistent with the specification. In re Am. Acad. of Sci. Tech.
Ctr., 367 F.3d 1359, 1364 (Fed. Cir. 2004). Under the broadest reasonable
interpretation, claim terms are given their ordinary and customary meaning,
as would be understood by one of ordinary skill in the art in the context of
the entire disclosure. In re Translogic Tech., Inc., 504 F.3d 1249, 1257
(Fed. Cir. 2007).
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The term “market conditions” is not expressly defined in Appellant’s
claims or Specification. However, the term “market conditions” is described
broadly as “given certain conditions” that may include, for example:
“advertiser data, historic event data, user data, real-time event data,
contextual data, and third-party commercial data.” Spec. ¶¶ 2–3, 5,
Abstract. According to Appellant’s Specification, “historic event data” may
include, for example: “weather data, events data, local news data, or some
other type of data” such as “response rates to certain types of advertisements
[that] may be correlated to stock market movements.” Spec. ¶ 58.
Likewise, real-time data may include “information about the Internet
Protocol (IP) address, context of an ad and/or ad placement, a user’s history,
geo-location information of the user, social behavior, inferred demographics
or some other type of data.” Spec. ¶ 67. Similarly, user’s behavior may
include, for example: “log ad impressions, user clicks, and user actions,”
i.e., “an advertisement clickthrough [clickrate], [] webpage visit, transaction
or purchase, or third party data associated with the user.” Spec. ¶ 98, 108.
Based on Appellant’s Specification, the term “market conditions” can
be broadly, but reasonably, interpreted to encompass Galperin’s CTR (click-
through rate) or conversion rate, Galperin’s use of different models to
compute an estimate of CTR and Galperin’s ad management (AM)
functionality 108, shown in Figure 1, used to “compare the performance of
the different models and select the model that appears to be doing the best
job at modeling the performance of the advertisement.” Galperin 25:15–30.
Because “Galperin who already teaches computation of predicted
performance (i.e. analogous to Scholl’s expected value) of ad placement by a
specific selected algorithm” in the context of an ad exchange, Scholl is only
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relied upon for teaching “automatically selecting and presenting . . . a
recommended bid amount . . . based on computation of expected value
[predicted performance] and/or budgetary considerations,” as recognized by
the Examiner. Ans. 9; see Scholl 7:1–32.
For these reasons, we are not persuaded of Examiner error.
Accordingly, we sustain the Examiner’s obviousness rejection of
independent claim 1 and its dependent claims 2–4, 24, and 25, which
Appellant does not argue separately. For the same reasons discussed, we
also sustain the Examiner’s obviousness rejection of dependent claims 5, 6,
7, and 23.

CONCLUSION
On the record before us, we conclude Appellant has not demonstrated
the Examiner erred in rejecting claims 1–7 and 23–25 under 35 U.S.C. § 101
and under 35 U.S.C. § 103(a), but has demonstrated the Examiner erred in
rejecting claims 1–7 and 23–25 under 35 U.S.C. § 112, first paragraph.

DECISION
As such, we AFFIRM the Examiner’s final rejection of claims 1–7
and 23–25 under 35 U.S.C. § 101 and under 35 U.S.C. § 103(a). However,
we REVERSE the Examiner’s final rejection of claims 1–7 and 23–25 under
35 U.S.C. § 112, first paragraph.
Because we have affirmed at least one ground of rejection with
respect to each claim on appeal, we affirm the Examiner’s decision rejecting
claims 1–7 and 23–25. See 37 C.F.R. § 41.50(a)(1).

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DECISION SUMMARY
Claims
Rejected
35 U.S.C.§ Basis Affirmed Reversed
1–7 and 23–25 101 non-statutory 1–7 and 23–
25

1–7 and 23–25 103 obviousness 1–7 and 23–
25

1–7 and 23–25 112, first
paragraph
written
description
1–7 and 23–
25
Overall Outcome 1–7 and 23–
25

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