DocumentCode :
593680
Title :
Towards hierarchical email recipient prediction
Author :
Bartel, J. ; Dewan, Prasun
Author_Institution :
Dept. of Comput. Sci., Univ. of North Carolina, Chapel Hill, NC, USA
fYear :
2012
fDate :
14-17 Oct. 2012
Firstpage :
50
Lastpage :
59
Abstract :
Previous email prediction algorithms generate individual predictions based on the past groupings of recipients or the contents of past emails. Our work builds on this research by (a) introducing new algorithms for extending and combining previous techniques and generating hierarchical recipient predictions and (b) comparing the previous algorithms with each other and the new algorithms. We used standard metrics and developed new metrics to measure three kinds of user effort: scanning predictions, selecting predictions, and manually entering recipients. The new metrics are based on a new abstract model of recipient prediction that applies to existing schemes and the new ones developed by us. Our evaluations, based on the Enron mail database and the Gmail user-interface for recipient prediction, show that (a) content is less effective than groups, (b) the combination of content and groups is less effective than groups alone, and (c) hierarchical recipient prediction reduces user effort.
Keywords :
electronic mail; graphical user interfaces; recommender systems; software metrics; Enron mail database; GUI; Gmail user-interface; abstract model; email prediction algorithms; hierarchical email recipient prediction; scanning predictions; selecting predictions; standard metrics; Atmospheric measurements; Extraterrestrial measurements; Jacobian matrices; Particle measurements; Predictive models; Space heating; email; privacy; recommender systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom), 2012 8th International Conference on
Conference_Location :
Pittsburgh, PA
Print_ISBN :
978-1-4673-2740-4
Type :
conf
Filename :
6450892
Link To Document :
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