Ex Parte Kashitani

Patent Trial and Appeal Board

Sep 2, 2016

12329782 (P.T.A.B. Sep. 2, 2016)

UNITED STA TES p A TENT AND TRADEMARK OFFICE
APPLICATION NO. FILING DATE FIRST NAMED INVENTOR
12/329,782 12/08/2008 Tatsuki KASHITANI
22850 7590 09/07/2016
OBLON, MCCLELLAND, MAIER & NEUSTADT, LLP,
1940 DUKE STREET
ALEXANDRIA, VA 22314
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.
452392US8PPMPH 9556
EXAMINER
ALATA, YASSIN
ART UNIT PAPER NUMBER
2427
NOTIFICATION DATE DELIVERY MODE
09/07/2016 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):
patentdocket@oblon.com
oblonpat@oblon.com
ahudgens@oblon.com
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
BEFORE THE PATENT TRIAL AND APPEAL BOARD
Ex parte T ATSUKI KASHIT ANI
Appeal2014-007051
Application 12/329,782
Technology Center 2400
Before CARLA M. KRIVAK, JOHN F. HORVATH, and
NABEEL U. KHAN, Administrative Patent Judges.
HORVATH, Administrative Patent Judge.
STATEMENT OF THE CASE
Appellant seeks review, under 35 U.S.C. § 134(a), of the Examiner's
rejection of claims 1-14. We have jurisdiction under 35 U.S.C. § 6(b).
We AFFIRM.
Appeal2014-007051
Application 12/329,782
SUMMARY OF THE INVENTION
The invention is directed to a content processing method that makes
recommendations reflecting viewer preferences. Spec. ,-r 1.
Claim 1, reproduced below, is illustrative of the claimed subject
matter:
1. A content processing apparatus comprising:
commercial specifying means for specifying types of
commercials included in content viewed by a user;
commercial preference information generating means for
generating commercial preference information by associating
each of the types of commercials with the number of times
commercials of a corresponding one of the types have been
viewed by the user in a predetermined period;
similarity computing means for generating program
commercial information of each of a plurality of pieces of
recorded content by associating each of types of commercials
inserted in each of the plurality of pieces of recorded content with
the number of commercials of a corresponding one of the types,
and computing a similarity between the program commercial
information and the commercial preference information,
wherein the similarity is computed by calculating an inner
product of a vector generated as the commercial preference
information and a vector generated as the program commercial
information, and the vector generated as the commercial
preference information is generated by dividing the number of
times commercials of each of types of commercials have been
viewed by the user in the predetermined period by a sum total of
the number of times commercials of each of types of
commercials have been viewed by the user in the predetermined
period; and
recommendation specifying means for specifying content
corresponding to the program commercial information having
the computed similarity equal to or larger than a predetermined
threshold value as content to be recommended for the user.
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Appeal2014-007051
Application 12/329,782
Kanno
Yamamoto
Turner
REFERENCES
US 2002/0016787 Al
US 2005/0165782 Al
US 2008/0263581 Al
REJECTIONS
Feb. 7,2002
July 28, 2005
Oct. 23, 2008
Claims 1-14 stand rejected under 35 U.S.C. § 103(a) as unpatentable
over Turner, Yamamoto, and Kanno. Final Act. 2.
ISSUES AND ANALYSIS
We have reviewed the Examiner's rejection in light of Appellant's
arguments that the Examiner has erred. We disagree with Appellant's
contentions, and adopt as our own the findings and reasoning set forth by the
Examiner in the Final Action and in the Examiner's Answer in response to
Appellant's Appeal Brief. We highlight the following for emphasis.
Issue 1: Whether the combination of Turner, Yamamoto, and
Kanno teaches or suggests calculating an inner product of a
commercial preference information (CPI) vector and a program
commercial information (PC!) vector, where the CPI vector
represents the viewing frequency of a plurality of types of
commercials over a predetermined period of time.
Appellant argues Kanno' s disclosure of storing, in a document profile
vector, the frequency of occurrence of keywords in the document has
"nothing to do with 'the number of times commercials of each of types of
commercials have been viewed by [a] user in [a] predetermined period,' as
recited in claim 1." App. Br. 14--15. Accordingly, Appellant argues the
Examiner erred in rejecting claim 1 because:
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Appeal2014-007051
Application 12/329,782
Kanno fails to teach or suggest, "the vector generated as the
commercial preference information is generated by dividing the
number of times commercials of each of types of commercials
have been viewed by the user in the predetermined period by a
sum total of the number of times commercials of each of types
of commercials have been viewed by the user in the
predetermined period," as recited in claim 1.
Id. at 15. We are not persuaded by Appellant's argument.
"Non-obviousness cannot be established by attacking references
individually where the rejection is based upon the teachings of a
combination of references." In re Merck & Co., Inc., 800 F.2d 1091, 1097
(Fed. Cir. 1986). Rather, the test for obviousness "is what the combined
teachings of the references would have suggested to those of ordinary skill
in the art." In re Keller, 642 F.2d 413, 425 (CCPA 1981). The Examiner
cites Turner, not Kanno, for teaching generating commercial product
information (CPI) and program commercial information (PCI). See Final
Act. 3. The Examiner cites Kanno simply for "teach[ing] the concept of
calculating an inner product of vectors and generating a vector by dividing a
frequency of occurrence by the sum total of frequency of occurrences."
Ans. 7. Thus, the Examiner finds:
the combination of Turner, Yamamoto, and Kanno discloses "the
similarity is computed by calculating an inner product of a vector
generated as the commercial preference information and a vector
generated as the program commercial information, and the vector
generated as the commercial preference information is generated
by dividing the number of times commercials of each of types of
commercials have been viewed by the user in the predetermined
period by a sum total of the number of times commercials of each
of types of commercials have been viewed by the user in the
predetermined period" as recited in claim 1.
Ans. 8-9.
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Appeal2014-007051
Application 12/329,782
Appellant does not persuasively show error in the Examiner's
findings. In the Reply, Appellant argues the combination of Turner,
Yamamoto, and Kanno fails to teach or suggest a CPI vector based on the
number of times different types of commercials have been viewed and
calculating a similarity as an inner product between CPI and PCI vectors.
Reply Br. 2-3. We disagree.
As noted above, the relevant question is whether the combined
teachings of the Turner, Yamamoto, and Kanno references would have
suggested these limitations to one of ordinary skill in the art. See Keller,
642 F.2d at 425. Turner teaches comparing local parameters to program
metadata in order "to target the commercials presented to the end viewer."
Turner ,-r 72. The local parameters can include user viewing and recording
history, as well as the types of locally stored commercials. Id. i-fi-1 72, 7 4.
The program metadata contains "characteristics of commercial segments
within the program," including the type of commercial. Id. i1i157, 70. Thus,
Turner teaches comparing CPI (commercial type, local viewing history) with
PCI (commercial type) in order to select commercials for the user to view.
Although, as the Examiner finds, Turner does not explicitly disclose how the
CPI and PCI information is compared. Final Act. 3.
However, the Examiner finds Yamamoto teaches a recommendation
engine that recommends content to a user based on "[t]he similarity of a
content meta vector associated with a candidate program ... relative to [a]
user preference vector." Yamamoto ,-r 5; Ans. 5; Final Act. 3--4. When the
similarity is greater than a threshold, the content is recommended to the user.
Id. ,-r 99. Yamamoto broadly describes content as any data that "was or will
be used (viewed or experienced) by a user," which description includes
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Appeal2014-007051
Application 12/329,782
commercial content. Id. ,-r 126. Yamamoto's content and preference vectors
contain weights based on "N pieces of individual information by using the
frequency of occurrence of each of the N pieces of individual information in
the content or based on a normalized value of the frequency of occurrence."
Id. ,-r 20. Yamamoto does not specifically disclose, however, that the
similarity between the content vector and user preference vector is
calculated as an inner product between the two vectors. See Final Act. 4.
The Examiner, therefore, relies on Kanno for teaching retrieving
similar documents by "calculat[ing] an inner product ... between [a]
retrieval condition feature vector ... and each document feature vector."
Kanno ,-r 57; Ans. 6-8; Final Act. 4. The inner product measures the
"[ s ]imilarity between the retrieval condition feature vector and the document
feature vector of each document." Id. ,-r 68. Although Kanno's disclosure
specifically pertains to retrieving similar documents, we agree with the
Examiner that Kanno's similarity calculation method "is a well-known
concept in the art, and can be applied to many situations." Ans. 7. Thus, a
person skilled in the art would have realized that Kanno' s method could
have been used to calculate the similarity between Yamamoto' s content and
user preference vectors, and Yamamoto' s content and user preference
vectors could have been generated from Turner's PCI information
(commercial type) and CPI information (commercial type, viewing history).
Consequently, we agree with, and adopt as our own the Examiner's
conclusion that the combination of Turner, Yamamoto, and Kanno teaches
or suggest to a person of ordinary skill in the art computing the similarity
between CPI and PCI vectors "by calculating an inner product of a vector
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Appeal2014-007051
Application 12/329,782
generated as the commercial preference information and a vector generated
as the program commercial information," as recited in claim 1. Ans. 8-9.
Accordingly, we sustain the Examiner's rejection of claim 1.
Appellant does not separately argue for the patentability of claims 2-14.
App. Br. 15. Accordingly, we sustain the Examiner's rejection of these
claims for the same reason.
DECISION
The Examiner's rejection of claims 1-14 is affirmed.
No time period for taking any subsequent action in connection with
this appeal may be extended under 37 C.F.R. § 1.136(a)(l )(iv).
AFFIRMED
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