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:
Aug. 07, 2018
Filed:
Jul. 28, 2015
Microsoft Technology Licensing, Llc, Redmond, WA (US);
Yelong Shen, Bothell, WA (US);
Xinying Song, Bellevue, WA (US);
Jianfeng Gao, Woodinville, WA (US);
Chenlei Guo, Redmond, WA (US);
Byungki Byun, Issaquah, WA (US);
Ye-Yi Wang, Redmond, WA (US);
Brian D. Remick, Morgan Hill, CA (US);
Edward Thiele, Mountain View, CA (US);
Mohammed Aatif Ali, Union City, CA (US);
Marcus Gois, San Jose, CA (US);
Yang Zou, Mountain View, CA (US);
Mariana Stepp, Santa Clara, CA (US);
Divya Jetley, Bellevue, WA (US);
Stephen Friesen, Dublin, CA (US);
MICROSOFT TECHNOLOGY LICENSING, LLC, Redmond, WA (US);
Abstract
Techniques for providing a people recommendation system for predicting and recommending relevant people (or other entities) to include in a conversation. In an exemplary embodiment, a plurality of conversation boxes associated with communications between a user and target recipients, or between other users and recipients, are collected and stored as user history. During a training phase, the user history is used to train encoder and decoder blocks in a de-noising auto-encoder model. During a prediction phase, the trained encoder and decoder are used to predict one or more recipients for a current conversation box composed by the user, based on contextual and other signals extracted from the current conversation box. The predicted recipients are ranked using a scoring function, and the top-ranked individuals or entities may be recommended to the user.