Email categorization using fast machine learning algorithms

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2534, Issue , 2002, Pages 316-323

  Yang, Jihoon ^a   Park, Sung Yong ^a  

^a Sogang University   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

ELECTRONIC MAIL; MACHINE LEARNING;

EMAIL CATEGORIZATION; EMAIL MESSAGES;

LEARNING ALGORITHMS;

EID: 35348872881     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-36182-0_31     Document Type: Conference Paper

References (14)

1. McCallum, A.: Bow: A toolkit for statistical language modeling, text retrieval, classification and clustering. http://www.cs.cmu.edu/∼mccallum/bow (1996)
2. Joachims, T.: A probabilistic analysis of the roccihio algorithm with tfidf for text categorization. Technical Report CMU-CS-96-118, Carnegie Mellon University, Pittsburgh, PA (1996)
3. Duda, R., Hart, P.: Pattern Classification and Scene Analysis. Wiley, New York (1973)
4. Mitchell, T.: Machine Learning. McGraw Hill, New York (1997)
5. Rocchio, J.: Relevance feedback in information retrieval. In: The SMART Retrieval System: Experiments in Automatic Document Processing. Prentice-Hall, Inc. (1971) 313–323
6. McCallum, A., Nigam, K.: A comparison of event models for naive bayes text classificaiton. In: Learning for Text CategorizationWorkshop, National Conference on Artificial Intelligence. (1998)
7. Salton, G.: Automatic Text Processing: the Transformation, Analysis, and Retrieval of Information by Computer. Addison-Wesley, Reading, Massachusetts (1989)
8. Korfhage, R.: Information Storage and Retrieval. Wiley, New York (1997)
9. Porter, M.: An algorithm for suffix stripping. Program 14 (1980) 130–137
10. Cover, T., Thomas, J.: Elements of Information Theory. John Wiley (1991)
11. Vapnik, V.: The Nature of Statistical Learning Theory. Springer Verlag (1995)
12. Yang, Y.: A re-examination of text categorization methods. In: Proceedings of the 22nd ACM SIGIR Conference. (1999) 42–49
13. Brutlag, J., Meek, C.: Challenges of the email domain for text classification. In: Proceedings of the Seventeenth International Conference on Machine Learning. (2000) 103–110
14. Sahami, M., Dumais, S., Heckerman, D., Horvitz, E.: A bayesian approach to filtering junk e-mail. In: Learning for Text Categorization Workshop, National Conference on Artificial Intelligence. (1998)