Ex Parte Kar et al

Patent Trial and Appeal Board

Jul 30, 2014

11675392 (P.T.A.B. Jul. 30, 2014)

UNITED STATES PATENT AND TRADEMARKOFFICE
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.
11/675,392 02/15/2007 Gautam Kar YOR920060782US1 6227
48063 7590 07/31/2014
RYAN, MASON & LEWIS, LLP
48 South Service Road
Suite 100
Melville, NY 11747
EXAMINER
ROBINSON, GRETA LEE
ART UNIT PAPER NUMBER
2169
MAIL DATE DELIVERY MODE
07/31/2014 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 GAUTAM KAR, RUCHI MAHINDRU,
ANCA SAILER, and XING WEI
____________________

Appeal 2012-000366
Application 11/675,392
Technology Center 2100
____________________

Before BRADLEY W. BAUMEISTER, ANDREW J. DILLON, and
IRVIN E. BRANCH, Administrative Patent Judges.

BRANCH, Administrative Patent Judge.

DECISION ON APPEAL
Appeal 2012-000366
Application 11/675,392

2
STATEMENT OF CASE
Appellants appeal under 35 U.S.C. § 134(a) from the Examiner’s
Final Rejection of claims 1–8 and 19–24. We have jurisdiction under
35 U.S.C. § 6(b). Claims 9–18 and 25–34 are canceled.
We reverse.
Illustrative Claim
Appellants’ disclosure relates to structuring free form heterogeneous
data, including obtaining the data, segmenting it into units, and
automatically labeling the units based on machine learning techniques.
Abstract.
Claim 1, reproduced below with the disputed limitation italicized, is
illustrative of the claimed subject matter:
1. A method, performed on a data processing system
comprising a memory and a data processor coupled to the
memory, of automatically structuring free form heterogeneous
data, the method comprising the steps of:
obtaining free form heterogeneous data;
segmenting the free form heterogeneous data into one or
more units, wherein the one or more units includes a sentence;
automatically labeling the one or more units based on one
or more machine learning techniques, wherein each unit is
associated with a label indicating an information structure type,
wherein automatically labeling one or more units includes
labeling a sentence with a label that indicates a type of
information provided by the sentence; and
structuring the one or more labeled units in a format to
facilitate one or more operations that use at least a portion of
the labeled units.

Appeal 2012-000366
Application 11/675,392

3
The Examiner rejected claims 1–8 and 19–24 under both 35 U.S.C.
§ 112, first paragraph, as failing to comply with the written description
requirement (Ans. 5), and 35 U.S.C. § 102(e) as anticipated by Viola
(US 2006/0245641 A1; published Nov. 2, 2006) (Ans. 6–9).

ANALYSIS
We have reviewed the Examiner’s rejections in light of Appellants’
arguments in the Appeal Brief (“App. Br.” filed June 13, 2011) and Reply
Brief (“Reply Br.” filed Aug. 12, 2011). We refer to the Briefs and the
Answer (“Ans.” mailed July 28, 2011) for the respective positions of
Appellants and the Examiner.
The 35 U.S.C. § 112, ¶ 1, Rejection
The Examiner finds the claims contain subject matter not described in
the Specification. Ans. 5. Specifically, the Examiner finds “wherein
automatically labeling one or more units includes labeling a sentence with a
label that indicates a type of information provided by the sentence” appears
not to be described or described clearly because “the disclosure does not
appear to use the term labeling sentences.” Id. While Appellants argue that
their Specification provides support for labeling sentences (App. Br. 9
(citing Spec. 9:22-26)), the Examiner finds that this portion of the
Specification is directed to a different embodiment of the present invention
(Ans. 10).
We disagree with the Examiner at least because, as Appellants point
out (App. Br. 9), the Specification recites “[f]or example, segmentation can
be based on sentences by identifying the punctuation in the free form data.”
(Spec. 9:24–25). We are unpersuaded by the Examiner that this section of
Appeal 2012-000366
Application 11/675,392

4
Appellants’ Specification is a different embodiment “directed to facilitating
technical assistance for one or more technology operations through use of an
annotation model.” Ans. 10. The portion of the Specification quoted is
introduced by, “[p]rinciples of the present invention may leverage different
ways to achieve segmentation.” Spec. 9:23–24. This passage demonstrates
that the segmentation based on sentences is applicable to the labeling
discussed elsewhere. See, e.g., Spec. 3:4–11.
Accordingly, we do not sustain the Examiner’s 35 U.S.C. § 112, ¶ 1,
rejection.
35 U.S.C. § 102 Rejection
The Examiner finds “Viola teaches Naive Bayes classifier to classify
(label) each word, however to improve recognition they consider assigning
labels to the word sequences [see: paragraph 0035], therefore the system
provides for blocks of words being labeled.” Ans. 11.
Appellants argue the Examiner erred in rejecting the claims as
anticipated by Viola. App. Br. 11–14; Reply Br. 4–5. Appellants state that
“while Viola may disclose labeling a word and sequence of words with
corresponding individual word labels, Viola does not disclose labeling a
sentence with a label, much less a label that indicates a type of information
provided by the sentence.” App. Br. 13.
We are persuaded the Examiner has erred. We do recognize that even
though a patent may not specifically disclose certain features, the reference’s
teachings may be taken in combination with knowledge of the skilled artisan
to put the artisan in possession of the claimed invention within 35 U.S.C.
§ 102. See In re Graves, 69 F.3d 1147, 1152 (Fed. Cir. 1995). In the
present case, though, the Examiner has failed to establish a factual basis
Appeal 2012-000366
Application 11/675,392

5
sufficient to support the conclusion that one skilled in the art would have
found Viola describes “wherein automatically labeling one or more units
includes labeling a sentence with a label that indicates a type of information
provided by the sentence.” The Examiner has not shown that Viola’s
mention of sentences at paragraph 49 (“A generative model defines a
language, and associates probabilities with each sentence in the language.”)
is sufficiently tied to Viola’s teaching of labeling sequences of words (see,
e.g., paragraph 58).
The question of whether Viola may potentially render claim 1 obvious
under 35 U.S.C. § 103(a) is not before us. The Board reviews the appealed
rejections for error based upon the issues identified by Appellants, and in
light of the arguments and evidence produced thereon. Ex Parte Frye,
94 USPQ2d 1072, 1075 (BPAI 2010) (citing In re Oetiker, 977 F.2d 1443,
1445). We therefore do not address this additional question.

DECISION
The Examiner’s rejections of claims 1–8 and 19–24 are reversed.

REVERSED

gvw