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Abstract: The explosive growth of on-line communication, in particular e-mail communication, makes it necessary to organize the information for faster and easier processing and searching. Storing e-mail messages into hierarchically organized folders, where each folder corresponds to a separate topic, has proven to be very useful. Previous approaches to this problem use Nave Bayes- or TF-IDF-style classifiers that are based on the unrealistic term independence assumption. These methods are also... (Update)
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BibTeX entry: (Update)
@misc{ itskevitch-automatic,
author = "Julia Itskevitch",
title = "Automatic Hierarchical E-Mail Classification Using Association Rules",
url = "citeseer.ist.psu.edu/itskevitch01automatic.html" }
Citations (may not include all citations):2319 Elements of information theory (context) - Cover, Thomas - 1991 ACM
2177 Programs for Machine Learning (context) - Quinlan - 1993
2133 Pattern Classification and Scene Analysis (context) - Duda, Hart - 1973
1543 Probabilistic Reasoning in Intelligent Systems: Networks of .. (context) - Pearl - 1991 ACM
1491 Learning internal representations by error propagation (context) - Rumelhart, Hinton et al. - 1996 ACM
1256 Introduction to Modern Information Retrieval (context) - Salton, McGill - 1983 ACM
921 Mining association rules between sets of items in large data.. - Agrawal, Imielinski et al. - 1993 ACM DBLP
910 Fast algorithms for mining association rules - Agrawal, Srikant - 1994 ACM
667 UCI repository of machine learning databases (context) - Merz, Murphy - 1996
416 Information Retrieval - Van Rijsbergen - 1979 ACM DBLP
376 Text categorization with support vector machines: learning w.. - Joachims - 1998
288 Relevance feedback in information retrieval (context) - Rocchio - 1971
268 Mining generalized association rules - Srikant, Agrawal - 1995 ACM DBLP
249 Mining frequent patterns without candidate generation - Han, Pei et al. - 2000 ACM DBLP
225 Data Mining: Concepts and Techniques (context) - Han, Kamber - 2001
215 A comparative study on feature selection in text categorizat.. - Yang, Pedersen - 1997 ACM DBLP
213 Discovery of multiple-level association rules from large dat.. - Han, Fu - 1995 ACM DBLP
161 Exploratory mining and pruning optimizations of constrained .. - Ng, Lakshmanan et al. - 1998 ACM
149 An evaluation of statistical approaches to text categorizati.. - Yang - 1999
138 Bayesian network classifiers - Friedman, Geiger et al. - 1997 ACM DBLP
135 Hierarchically classifying documents using very few words - Koller, Sahami - 1997 ACM DBLP
134 Modern Information Retrieval (context) - Baeza-Yates, Ribeiro-Neto - 1999 ACM DBLP
123 Toward optimal feature selection - Koller, Sahami - 1996 DBLP
103 Scattergather cluster based approach to browsing large docum.. - Karger, Tukey et al. - 1992
103 at forty: The independence assumption in information retriev.. (context) - Lewis, Bayes - 1998
91 Integrating classification and association rule mining - Liu, Hsu et al. - 1998 ACM DBLP
82 Information Retrieval : Data Structures & Algorithms (context) - Frakes, Baeza-Yates - 1992
76 A bayesian approach to filtering junk e-mail - Sahami, Dumais et al. - 1998
66 Learning rules that classify e-mail - Cohen - 1996
63 Threading electronic mail: A preliminary study - Lewis, Knowles - 1997
51 Classifying news stories using memory-based reasoning (context) - Masand, Lino et al. - 1992
44 An example-based mapping method for text categorization and .. (context) - Yang, Chute - 1994 ACM DBLP
42 An information theoretic approach to rule induction from dat.. (context) - Smyth, Goodman - 1992 ACM DBLP
36 and a usability case study for text categorization (context) - Ng, Goh et al. - 1997
34 Automatic retrieval with locality information using SMART (context) - Buckley, Salton et al. - 1992 DBLP
27 Text categorization of low quality images (context) - Ittner, Lewis et al. - 1995
24 Concept feature reagent (context) - Concept, re et al. - 1998
24 Structuring computer-mediated communications systems to avoi.. (context) - Hiltz, Turo - 1985
23 and signatures for navigating in text databases (context) - Chakrabarti, Dom et al. - 1997
21 Building hierarchical classifiers using class proximity - Wang, Zhou et al. - 1999 ACM DBLP
21 Text mining with decision rules and decision trees (context) - Apte, Damerau et al. - 1998
20 Partial classification using association rules - Ali, Manganaris et al. - 1997 DBLP
20 cient mining of emerging patterns: Discovering trends and di.. (context) - Dong, Li - 1999
15 Machine Learning applications in Expert Systems and Informat.. (context) - Forsyth, Rada - 1986
15 ifile: An application of machine learning to e-mail filterin.. - Rennie - 2000
14 Kluwer Academic Publisher (context) - Grossman, Frieder et al. - 1998
11 Athena: Mining-based interactive management of text database.. - Agrawal, Bayardo et al. - 2000
10 Incremental learning in swiftFile - Segal, Kephart - 2000 ACM DBLP
9 Predictive Data Mining (context) - Weiss, Indurkhua - 1998 ACM
9 Extracting collocations from text corpora - Lin - 1998
8 Discovering unordered and ordered phrase association pattern.. - Fujino, Arimura et al. - 2000 ACM DBLP
8 Growing decision trees on support-less association rules - Wang, Zhou et al. - 2000 ACM DBLP
8 Ishmail: Immediate identification of important information - Helfman, Isbell - 1995
8 Text categorization: A survey (context) - Aas, Eikvil - 1999
7 A comparison of event models for Nave bayes text classificat.. (context) - McCallum, Nigam - 1998
7 Minimizing information overload: the ranking of electronic m.. - Losee - 1989 ACM
6 The nature of statistical learning theory (context) - Vapnic - 1995 ACM
5 Looking for needles in a haystack Or Locating interesting co.. (context) - Choueka - 1988
5 A comparative study of classification-based personal e-mail .. - Diao, Lu et al. - 2000
5 AIM: A new approach for meeting information needs (context) - Barrett, Selker - 1995
4 Extending Nave bayes classifiers using long itemsets - Meretakis, Wuthrich - 1999
4 Using qualitative models to guide induction learning (context) - Clark, Matwin - 1993
4 mail authorship (context) - Vel - 2000
4 Making use of the most expressive jumping emerging patterns .. - Li, Dong et al. - 2000 ACM DBLP
4 Representation of electronic mail filtering profiles: a user.. - Pazzani - 2000 DBLP
4 Classification based on multiple association rules (context) - Li - 2001
3 Scalable associationbased text classification - Meretakis, Fragoudis et al. - 2000
3 Swiftfile: An intelligent assistant for organizing e-mail - Segal, Kephart - 2000
1 Knowledge-lite extraction of multi-word units with language .. - Merkel, Andersson - 2000
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