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Abstract: Electronic mail offers the promise of rapid communication of essential information. However, electronic mail is also used to send unwanted messages. A variety of approaches can learn a profile of a user's interests for filtering mail. Here, we report on a usability study that investigates what types of profiles people would be willing to use to filter mail. Keywords Mail Filtering; User Studies 1. INTRODUCTION While electronic mail offers the promise of rapid communication of essential... (Update)
Context of citations to this paper: More
...message. Separating messages into several groups by topic can also help a user to prioritize the e mail or suggest further actions [Paz00] HT85] suggest that information inundation may cause information entropy, when incoming messages are not su#ciently organized by topic...
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BibTeX entry: (Update)
M. Pazzani and D. Billsus, "Representation of Electronic Mail Filtering Profiles: A User Study," Proc. ACM Conf. Intelligent User Interfaces, ACM Press, NewYork, 2000. http://citeseer.ist.psu.edu/pazzani00representation.html More
@inproceedings{ pazzani00representation,
author = "Michael J. Pazzani",
title = "Representation of electronic mail filtering profiles: a user study",
booktitle = "Intelligent User Interfaces",
pages = "202-206",
year = "2000",
url = "citeseer.ist.psu.edu/pazzani00representation.html" }
Citations (may not include all citations):2177 Programs for Machine Learning (context) - Quinlan - 1993
2133 Pattern classification and scene analysis (context) - Duda, Hart - 1973
288 Relevance feedback information retrieval (context) - Rocchio - 1971
120 Inductive learning algorithms and representations for text c.. (context) - Dumais, Platt et al. - 1998
110 Training algorithms for linear text classifiers - Lewis, Schapire et al. - 1996
91 Learning and Revising User Profiles: The identification of i.. - Pazzani, Billsus - 1997
76 A Bayesian approach to filtering junk e-mail - Sahami, Dumais et al. - 1998
12 Artificial Intelligence Review (context) - Pazzani, in
1 Learning Rules that Classify E-Mail In the 1996 AAAI Spring .. (context) - Cohen - 1996
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