Daryl J Pregibon

6480844, Nov 12, 2002

Mar 25, 1999

09/276448

Corinna Cortes - New York NY
Daryl Pregibon - Summit NJ

ATT Corp. - New York NY

G06F 1730

707 5, 379 8822, 379 8823, 379 8825

A method provides for mining information from large volumes of data regarding transactions. The method provides for inferring a behavioral characteristic of a party to the transaction based on a large volume of data concerning a multitude of parties. That inferred characteristic may be dynamic in nature.

6539391, Mar 25, 2003

Aug 13, 1999

09/373823

William H. DuMouchel - Chatham NJ
Christopher T. Volinsky - Morris Plains NJ
Theodore J. Johnson - New York NY
Corinna Cortes - New York NY
Daryl Pregibon - Summit NJ

ATT Corp. - New York NY

G06F 1730

707101, 707100, 707102, 707103, 707 2

Apparatus and method for summarizing an original large data set with a representative data set. The data elements in both the original data set and the representative data set have the same variables, but there are significantly fewer data elements in the representative data set. Each data element in the representative data set has an associated weight, representing the degree of compression. There are three steps for constructing the representative data set. First, the original data elements are partitioned into separate bins. Second, moments of the data elements partitioned in each bin are calculated. Finally, the representative data set is generated by finding data elements and associated weights having substantially the same moments as the original data set.

7827060, Nov 2, 2010

Dec 30, 2005

11/321064

Daniel Wright - Millbrae CA, US
Daryl Pregibon - Summit NJ, US
Diane Tang - Portola Valley CA, US

Google Inc. - Mountain View CA

G06Q 30/00

705 144, 705 1449, 705 1445, 705 1452, 705 1466, 705 1467

A system obtains a first parameter (QP) associated with a quality of an advertisement among multiple advertisements, where the first quality parameter (QP) does not include a click through rate (CTR). The system functionally combines the first quality parameter (QP) with at least one other parameter and uses the functional combination to filter, rank or promote the advertisement among the multiple advertisements.

8065184, Nov 22, 2011

Dec 30, 2005

11/321076

Daniel Wright - Millbrae CA, US
Daryl Pregibon - Summit NJ, US
Diane Tang - Portola Valley CA, US

Google Inc. - Mountain View CA

G06Q 30/00
G05B 19/418

705 1441, 705 1451

A system obtains ratings associated with a first set of advertisements hosted by one or more servers, where the ratings indicate a quality of the first set of advertisements. The system observes multiple different first user actions associated with user selection of advertisements of the first set of advertisements and derives a statistical model using the observed first user actions and the obtained ratings. The system further observes second user actions associated with user selection of a second advertisement hosted by the one or more servers and uses the statistical model and the second user actions to estimate a quality of the second advertisement.

8090703, Jan 3, 2012

Feb 6, 2009

12/367437

Ashish Agarwal - Sunnyvale CA, US
Eric Bauer Arbanovella - Boonville CA, US
Diane Lambert - Berkeley Heights NJ, US
Ilia Mirkin - New York NY, US
Michael M. Meyer - Seattle WA, US
James A. Morrison - San Francisco CA, US
Daryl Pregibon - Hoboken NJ, US
Susan Shannon - San Mateo CA, US
Diane L. Tang - Palo Alto CA, US

Google Inc. - Mountain View CA

G06F 17/30

707707, 707661, 707706, 707713, 707709, 707711, 707712, 707722, 707736, 707758, 707781, 707791, 707802

User queries are received, with each query requesting a service from a server. Overlapping experiments are performed on at least a portion of the queries, with each experiment modifying one or more parameters associated with the queries or parameters associated with processing of the queries, and with the experiments organized into layers. Two or more experiments in different layers are allowed to be performed on the same query, and for any given layer, at most one experiment is allowed to be performed on the same query.

8429012, Apr 23, 2013

Sep 24, 2010

12/890271

Daniel Wright - Millbrae CA, US
Daryl Pregibon - Summit NJ, US
Diane Tang - Portola Valley CA, US

Google Inc. - Mountain View CA

G06Q 30/00

705 1441, 705 1442

A system obtains a first parameter (QP) associated with a quality of an advertisement among multiple advertisements, where the first quality parameter (QP) does not include a click through rate (CTR). The system functionally combines the first quality parameter (QP) with at least one other parameter and uses the functional combination to filter, rank or promote the advertisement among the multiple advertisements.

20070156887, Jul 5, 2007

Dec 30, 2005

11/321046

Daniel Wright - Millbrae CA, US
Daryl Pregibon - Summit NJ, US
Diane Tang - Portola Valley CA, US

G06F 15/173

709224000

A system provides one or more advertisements to users in response to search queries and logs user behavior associated with user selection of the one or more advertisements. The system also logs features associated with selected ones of the one or more advertisements, or associated with the search queries. The system further uses a statistical model and the logged user behavior to estimate quality scores associated with the selected advertisements and aggregates the estimated quality scores. The system predicts the quality of another advertisement using the aggregated quality scores.

20110119126, May 19, 2011

Nov 19, 2009

12/621966

John B. Park - Irvine CA, US
Daryl Pregibon - Hoboken NJ, US
Neha Singh - New York NY, US
Leo Deegan - San Francisco CA, US

GOOGLE INC. - Mountain View CA

G06Q 30/00

705 1445, 705 1441

Methods, systems, and apparatuses for online monitoring systems to determine offline advertising effectiveness. Information related to an advertisement for a product is received. The advertisement is presented through offline media. The information includes an advertising schedule. Communications related to the product that are received from the consumers in the market at the time the advertisement is presented, are detected. Data responsive to the detected communications are collected; the data represent a number of consumers in the market. A statistical correlation between the collected data and the advertising schedule is determined and provided to the advertiser as a report of the effectiveness of the advertising.