Predicting email recipients

Zvi Sofershtein, Sara Cohen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

The ability to accurately predict recipients of an email, while it is being composed, is of great practical importance for two reasons. First, prediction of recipients allows for effective "auto-complete" of this field, thereby improving user experience and reducing the overhead of manual typing of the recipient. Second, this capability allows the system to alert the user when she has typed unlikely recipients. Such alerts can help avoid human error that might result in forgetting relevant recipients, or, even worse, disclosure of personal or classified information. In this demonstration, a system that effectively predicts email recipients, given an email history, will be exhibited. The system takes into consideration a variety of email related features to achieve high accuracy. Extensive experimentation on diverse email corpora has shown that our system adapts well to a variety of domains (such as business, personal and political email). Conference participants will be able to view real emails sent, and to observe how well our system predicted the recipients. In addition, they will be able to "impersonate" users whose email history is already available to the system, to compose a new email, and to view the recipient predictions.

Original languageAmerican English
Title of host publicationProceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015
EditorsJian Pei, Jie Tang, Fabrizio Silvestri
PublisherAssociation for Computing Machinery, Inc
Pages761-764
Number of pages4
ISBN (Electronic)9781450338547
DOIs
StatePublished - 25 Aug 2015
EventIEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015 - Paris, France
Duration: 25 Aug 201528 Aug 2015

Publication series

NameProceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015

Conference

ConferenceIEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015
Country/TerritoryFrance
CityParis
Period25/08/1528/08/15

Bibliographical note

Funding Information:
V. ACKNOWLEDGEMENTS The authors were partially supported by the Israel Science Foundation (Grant 1467/13) and the Ministry of Science and Technology (Grant 3-9617).

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