Ex Parte Zhang

Patent Trial and Appeal Board

Apr 6, 2016

12764732 (P.T.A.B. Apr. 6, 2016)

UNITED STA TES p A TENT AND TRADEMARK OFFICE
APPLICATION NO. FILING DATE FIRST NAMED INVENTOR
121764,732 04/21/2010 Qiong Zhang
97531 7590 04/06/2016
Mauriel Kapouytian Woods LLP
15 W. 26th Street
7th Floor
New York, NY 10010
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
ATTORNEY DOCKET NO. CONFIRMATION NO.
10033-2004200 7941
EXAMINER
BRANDENBURG, WILLIAM A
ART UNIT PAPER NUMBER
3681
MAILDATE DELIVERY MODE
04/06/2016 PAPER
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.
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
BEFORE THE PATENT TRIAL AND APPEAL BOARD
Ex parte QIONG ZHANG
Appeal 2014-001498 1,2
Application 12/764,732
Technology Center 3600
Before MICHAEL C. ASTORINO, PHILIP J. HOFFMANN, and
BRUCE T. WIEDER, Administrative Patent Judges.
HOFFMANN, Administrative Patent Judge.
DECISION ON APPEAL
STATEivIENT OF THE CASE
Appellant appeals under 35 U.S.C. § 134(a) from the rejection of
claims 1-20. We have jurisdiction under 35 U.S.C. § 6(b ).
We REVERSE.
According to Appellant, "the invention provide methods and systems
for use in association with online advertising, relating to use of serving
1 Our decision references Appellant's Specification ("Spec.," filed Apr. 21,
2010), Appeal Brief ("Appeal Br.," filed June 24, 2013), and Reply Br.
("Reply Br.," filed Nov. 11, 2013), as well as the Final Office Action ("Final
Action," mailed Jan. 24, 2013) and the Examiner's Answer ("Answer,"
mailed Sept. 13, 2013).
2 According to Appellant, "[ t ]he real party in interest is Yahoo! Inc."
Appeal Br. 3.
Appeal2014-001498
Application 12/764,732
thresholds, associated with predicted click through rates, and delivery
policies, associated with advertising inventory serving and distribution."
Spec. i-f 6. We reproduce, below, independent claim 1 as representative of
the appealed claims.
1. A method comprising:
using one or more computers, during an offline period,
initially determining a set of serving thresholds to be utilized in
online advertisement serving, wherein a serving threshold is
associated with a minimum anticipated click through rate;
using one or more computer computers, [3J during an
offline period, initially determining a set of delivery policies,
wherein a delivery policy is associated with one or more rules
relating to serving of advertisements in accordance with required
or optimal distribution of advertising inventory across serving
opportunities;
using one or more computers, during, and based at least in
part on information obtained during, an online period, adjusting
at least one of the set of serving thresholds to determine at least
one adjusted serving threshold, and adjusting at least one of the
set of delivery policies to determine at least one adjusted delivery
policy; and
using one or more computers, during an online period,
utilizing a machine learning-based model in decision-making
with regard to serving of online advertisements in connection
with serving opportunities based at least in part on the at least
one adjusted serving threshold and the at least one adjusted
delivery policy, wherein the machine learning-based model is
trained during an offline period, wherein an online period is a
period of active advertisement serving in which the model is
utilized.
Appeal Br. 23, Claims App.
3 We note that the recitation of "one or more computer computers" appears
to be a typographical error. Thus, we interpret the phrase as "one or more
computers."
2
Appeal2014-001498
Application 12/764,732
REJECTION AND PRIOR ART
The Examiner rejects claims 1-20 under 35 U.S.C. § 102(e) as
anticipated by Sanghavi (US 2011/0112900 Al, pub. May 12, 2011). See
Final Action 2-26; see also Answer 2.
ANALYSIS
As set forth above, independent claim 1, from which claims 2-15
depend, recites the following:
... during an offline period, initially determining a set of
serving thresholds to be utilized in online advertisement serving,
wherein a serving threshold is associated with a minimum
anticipated click through rate; [and]
. . . during, and based at least in part on information
obtained during, an online period, adjusting at least one of the set
of serving thresholds to determine at least one adjusted serving
threshold.
Appeal Br. 23, Claims App. Independent claim 16, from which claims 17-
19 depend, and independent claim 20, recite similar limitations. See id. at
26-27. Thus, each of the claims requires, in some form, 1) determining
during an offline period a set of serving thresholds associated with a
minimum anticipated click through rate, and 2) adjusting at least one of the
set of serving thresholds (associated with a minimum anticipated click
through rate) during an online period. Appellant argues that Sangha vi does
not teach these limitations. See id. at 11-12. In response to Appellant's
argument, the Examiner finds that paragraphs 16, 22, and 26 of Sanghavi
disclose the limitations. See Answer 10-11.
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Appeal2014-001498
Application 12/764,732
Based on our review of the cited portion of Sanghavi, however, we
determine that the Examiner does not establish by a preponderance of the
evidence that Sanghavi discloses 1) determining during an offline period a
set of serving thresholds associated with a minimum anticipated click
through rate, and 2) adjusting at least one of the set of serving thresholds
(associated with a minimum anticipated click through rate) during an online
period. For example, the only discussion of "click through rates" in
Sanghavi appears to be provided in paragraph 26, which is cited by the
Examiner. However, it is not clear to us that there is a minimum anticipated
click through rate that is determined, or that any adjustment of the minimum
anticipated click through rate occurs. Rather, Sangha vi's paragraph 26
appears to discuss real-time or frequent monitoring of advertisement
performance by tracking the actual click through rates, to identify
underperformance or overperformance relative to an advertisement
agreement. There does not appear to be any discussion of a predicted,
minimum anticipated click through rate, or that there is any update of the
predicted anticipated click through rate. The other paragraphs identified by
the Examiner (i.e., paragraphs 16 and 22) discuss modification of the
advertisement campaign, without any clear indication of either 1)
determining a set of serving thresholds associated with a minimum
anticipated click through rate, or 2) adjusting at least one of the set of
serving thresholds (associated with a minimum anticipated click through
rate).
Thus, for the above reasons, we do not sustain the anticipation
rejection of claims 1-20.
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Appeal2014-001498
Application 12/764,732
DECISION
We reverse the Examiner's rejection of claims 1-20 under 35 U.S.C.
§ 102(e).
REVERSED
5