The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Jul. 21, 2015
Filed:
Aug. 30, 2010
Abraham Bagherjeiran, Sunnyvale, CA (US);
Renjie Tang, San Jose, CA (US);
Zengvan Zhang, San Jose, CA (US);
Andrew Hatch, Oakland, CA (US);
Adwait Ratnaparkhi, San Jose, CA (US);
Ralesh Parekh, San Jose, CA (US);
Abraham Bagherjeiran, Sunnyvale, CA (US);
Renjie Tang, San Jose, CA (US);
Zengvan Zhang, San Jose, CA (US);
Andrew Hatch, Oakland, CA (US);
Adwait Ratnaparkhi, San Jose, CA (US);
Ralesh Parekh, San Jose, CA (US);
Yahoo! Inc., Sunnyvale, CA (US);
Abstract
A method for adaptive display of internet advertisements to look-alike users using a desired user profile dataset as a seed to machine learning modules. Upon availability of a desired user profile, that user profile is mapped other look-alike users (from a larger database of users). The method proceeds to normalize the desired user profile object, proceeds to normalize known user profile objects, then seeding a machine-learning training model with the normalized desired user profile object. A scoring engine uses the normalized user profiles for matching based on extracted features (i.e. extracted from the normalized user profile objects). Once look-alike users have been identified, the internet display system may serve advertisements to the look-alike users, and analyze look-alike users' behaviors for storing the predicted similar user profile objects into the desired user profile object dataset, thus adapting to changing user behavior.