Ex Parte Li et al

Patent Trials and Appeals BoardMar 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. Â§ 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. Â§ 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. 2 Appeal2018-002487 Application 14/045,656 References and Rejection Claims 1-20 stand rejected under 35 U.S.C. Â§ 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. Â§ 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 4