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Abstract: The rise of the World Wide Web and the ever-increasing amounts of machine-readable text has caused text classification to become a important aspect of machine learning. One specific application that has the potential to affect almost every user of the Internet is e-mail filtering. The WorldTalk Corporation estimates that over 60 million business people use e-mail [6]. Many more use e-mail purely on a personal basis and the pool of e-mail users is growing daily. And yet, automated techniques for ... (Update)
Context of citations to this paper: More
.... incoming messages into folders on specific topics, sometimes recommending further actions on the part of a user [5, 10, 14, 32, 33, 42, 51, 52, 54, 55, 56, 59, 60] in e#ect, this framework seeks to automate a kind of filing system that many users implement manually. There...
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BibTeX entry: (Update)
Rennie, Jason. "ifile: An Application of Machine Learning to E-Mail Filtering." CMU, December, 1998. http://citeseer.ist.psu.edu/rennie00ifile.html More
@inproceedings{ rennie00ifile,author = "Jason D. M. Rennie"
,title = "{i}file: An Application of Machine Learning to Mail Filtering"
,booktitle = "Proceedings of the KDD-2000 Workshop on Text Mining"
,year = 2000,
url = "citeseer.ist.psu.edu/rennie00ifile.html" }
Citations (may not include all citations):376 Text categorization with support vector machines: Learning w.. - Joachims - 1998
318 The Psychology of Human Computer Interaction (context) - Card, Moran et al. - 1983
72 Bow: A toolkit for statistical language modeling (context) - McCallum - 1996
66 Learning rules that classify e-mail - Cohen - 1996
63 Threading electronic mail: A preliminary study - Lewis, Knowles - 1997
48 Maximum entropy discrimination - Jaakkola, Meila et al. - 1999 ACM DBLP
48 Newsweeder: Learning to lter netnews (context) - Lang - 1995
41 Feature selection in statistical learning of text categoriza.. (context) - Yang, Pedersen - 1997
37 line new event detection and tracking - Allan, Papka et al. - 1998
32 A comparison of event models for naive bayes text classicati.. (context) - McCallum, Nigam - 1998
26 Support vector machines for spam categorization (context) - Drucker, Wu et al. - 1999
23 Mailcat: An intelligent assistant for organizing e-mail - Segal, Kephart - 1999 DBLP
16 Improving text categorization methods for event tracking - Yang, Ault et al. - 2000 ACM DBLP
6 Error-correcting output coding for text classication (context) - Berger - 1999
5 A bayesian approach to ltering junk e-mail (context) - Sahami, Dumais et al. - 1998
5 Feature engineering for text classication (context) - Scott, Matwin - 1999
2 Ishmail: Immediate identication of important information (context) - Helfman, Isbell - 1995
1 Incremental learning in swiftle (context) - Segal, Kephart - 2000
1 Worldtalk releases rst Internet e-mail corproate usage repor.. (context) - Harris, Clark - 1999
The graph only includes citing articles where the year of publication is known.
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TopCat: Data Mining for Topic Identification in a Text Corpus - Clifton, Cooley, Rennie (2002) (Correct)
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