Ex Parte Li et al

Patent Trials and Appeals Board

Mar 26, 2019

14045656 - (D) (P.T.A.B. Mar. 26, 2019)

UNITED STA TES p A TENT AND TRADEMARK OFFICE
APPLICATION NO. FILING DATE
14/045,656 10/03/2013
106592 7590 03/28/2019
Klarquist Sparkman, LLP (SAP)
121 SW Salmon Street, Suite 1600
Portland, OR 97204
FIRST NAMED INVENTOR
Wen-SyanLi
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.
8880-100997-01 7660
EXAMINER
ALLEN, NICHOLAS E
ART UNIT PAPER NUMBER
2154
NOTIFICATION DATE DELIVERY MODE
03/28/2019 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):
docketing@klarquist.com
AS CChair@klarquis t. com
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
BEFORE THE PATENT TRIAL AND APPEAL BOARD
Ex parte WEN-SY AN LI and YU CHENG
Appeal 2018-002487
Application 14/045,656 1
Technology Center 2100
Before CAROLYN D. THOMAS, IRVINE. BRANCH, and
JON M. JURGOV AN, Administrative Patent Judges.
BRANCH, Administrative Patent Judge.
DECISION ON APPEAL
Appellants appeal under 35 U.S.C. § 134(a) from a final rejection of
claims 1-20, which are all of the claims pending in the application. We
have jurisdiction under 35 U.S.C. § 6(b ).
We REVERSE.
1 According to Appellants, the real party in interest is SAP SE. App. Br. 2.
Appeal2018-002487
Application 14/045,656
Technology
The application relates to predicting missing values in a database.
Spec. ,r 2.
Illustrative Claim
Claim 1 is illustrative and reproduced below with the limitations at
issue emphasized:
1. A method, comprising:
in a dataset including a plurality of records, at least one of
the plurality of records including one or more field having a
missing value, wherein completing the dataset includes:
selecting a target record from the dataset, the target record
being one of the plurality of records including a missing value;
partitioning a portion of the plurality of records of the
dataset into at least two groups of columns including co-related
data, the portion of the plurality of records being selected from
the plurality of records and including records having a value for
a same field as the missing value in the target record;
predicting the missing value based on a relationship
between fields in each of the at least two groups of columns
associated with the partitioned records; and
setting the field including the missing value of the target
record to the predicted value;
wherein predicting the missing value includes:
generating a first linear function based on a first
type of co-related data;
generating a second linear function based on a
second type of co-related data;
generate a bi-local linear local model based on the
first linear function and the second linear function; and
predicting the missing value using the bi-local
linear local model.
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Appeal2018-002487
Application 14/045,656
References and Rejection
Claims 1-20 stand rejected under 35 U.S.C. § 103 as unpatentable
over Caruana (US 6,047,287; Apr. 4, 2000) and Lin et al. (US 8,443,013 Bl;
Mar. 14, 2013) ("Lin"). Final Act. 2-18.
ANALYSIS
We have reviewed the Examiner's rejections in light of Appellants'
arguments. We have considered in this Decision only those arguments
Appellants actually raised in the Briefs. Any other arguments Appellants
could have made but chose not to make in the Briefs are deemed to be
waived. See 37 C.F.R. § 4I.37(c)(l)(iv).
Claim 1 recites generating first and second linear functions based on
two types of "co-related data," and generating "a bi-local linear local model
based on the first linear function and the second linear function," which is
then used to predict a missing value in a dataset.
Appellants initially argue error based on the Examiner's finding that
"the bi-local linear local model 'is just a form of modeling which could have
been readily implemented by Lin."' App. Br. 9 ( quoting with emphasis
Advisory Action 2 (mailed June 2, 2017) ("A bi-local linear model is just a
form of modeling which could have been readily implemented by Lin et al.
in predicting missing values.")).
The Examiner maintains the rejection based on a finding that "[a] bi-
local linear local model is an application of linear regression." Ans. 8.
Appellants then argue that the Examiner has mapped one of the first
or second of claim 1 's linear functions to Lin's regression, so the same
regression cannot also be the "bi-local linear local model," which is "based
on the first linear function and the second linear function." Reply Br. 2-3.
3
Appeal2018-002487
Application 14/045,656
We are persuaded by Appellants' argument. We do not find an
adequate explanation for how Lin discloses predicting a missing value based
on a "bi-local linear local model," which is based on two linear functions as
claimed. The Examiner does not cite Caruana for this limitation, nor does
the Examiner adequately explain how the missing limitation would have
been obvious to one of ordinary skill in art at the time of Appellants'
invention. See generally Final Act. 2-5; Advisory Action 2; Ans. 8.
Accordingly, on this record, we do not sustain the Examiner's
rejection of claim 1. We also do not sustain the rejection of independent
claims 10 and 19, which include commensurate recitations. We also do not
sustain the rejection of the dependent claims for the same reason.
DECISION
For the reasons above, we reverse the Examiner's decision rejecting
claims 1-20.
REVERSED
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