Unformatted text preview: ction. AI Magazine, 184:65 79, 1997.
9 D. Cohn, L. Atlas, and R. Ladner. Improving generalization with active learning. Machine Learning,
152:201 221, 1994.
10 DARPA, editor. Proceedings of the 6th Message Understanding Conference, San Mateo, CA, 1995. Morgan
Kaufman. 11 T. Joachims. A probabilistic analysis of the Rocchio
algorithm with TFIDF for text categorization. In Proceedings of the Fourteenth International Conference on
Machine Learning, pages 143 151, San Francisco, CA,
1997. Morgan Kaufman.
12 H. Kautz, editor. Papers from the AAAI 1998 Workshop on Recommender Systems, Madison, WI, 1998.
13 A. Kent and et al. Use of Library Materials: The University of Pittsburgh Study. Dekker, New York, 1979.
14 Ron Kohavi, Barry Becker, and Dan Sommer eld. Improving simple Bayes. In Proceedings of the European
Conference on Machine Learning, 1997.
15 N. Kushmerick, K. Weld, and R. Doorenbos. Wrapper
induction for information extraction. In Proceedings of
the Fifteenth International Joint Conference on Arti cial Intelligence, pages 729 735, Nagoya, Japan, 1997.
16 K. Lang. NewsWeeder: Learning to lter netnews. In
Proceedings of the Twelfth International Conference on
Machine Learning, pages 331 339, San Francisco, CA,
1995. Morgan Kaufman.
17 Wendy Lehnert and Beth Sundheim. A performance
evaluation of text-analysis technologies. AI Magazine,
123:81 94, 1991.
18 D. D. Lewis and J. Catlett. Heterogeneous uncertainty
sampling for supervised learning. In Proceedings of the
Eleventh International Conference on Machine Learning, pages 148 156, San Francisco, CA, July 1994. Morgan Kaufman.
19 Ray Liere and Prasad Tadepalli. Active learning with
committees for text categorization. In Proceedings of
the Fourteenth National Conference on Arti cial Intelligence, pages 591 596, 1997.
20 Pattie Maes. Agents that reduce work and information overload. Communications of the Association for
Computing Machinery, 377:31 40, 1994.
21 A. McCallum and K. Nigam. A comparison of event
models for naive Bayes text classi cation. In Papers
from the AAAI 1998 Workshop on Text Categorization,
pages 41 48, Madison, WI, 1998.
22 K. McCook and G. O. Rolstad, editors. Developing
Readers' Advisory Services: Concepts and Committments. Neal-Schuman, New York, 1993.
23 T. Mitchell. Machine Learning. McGraw-Hill, New
York, NY, 1997.
24 K. Nigam, A. McCallum, S. Thrun, and T. Mitchell.
Learning to classify text from labeled and unlabeled
documents. In Proceedings of the Fifteenth National
Conference on Arti cial Intelligence, pages 792 799,
Madison, WI, July 1998.
25 M. Pazzani and D. Billsus. Learning and revising user
pro les: The identi cation of interesting web sites. Machine Learning, 273:313 331, 1997.
26 M. Pazzani, J. Muramatsu, and D. Billsus. Syskill &
Webert: Identifying interesting web sites. In Proceedings of the Thirteenth National Conference on Arti cial
Intelligence, pages 54 61, Portland, OR, August 1996. 27 P. Resnik and H. R. Varian. Introduction to the special
section on recommender systems. Communications of
the Association for Computing Machinery, 403:56 59,
28 G. Salton and C. Buckley. Improving retrieval performance by relevance feedback. Journal of the American
Society for Information Science, 41:288 297, 1990....
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