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Abstract: . Information filtering has become an important component of modern information systems due to significant increase in its applications. The objective of an information filtering is to classify/categorize documents as they arrive into the system. In this paper, we investigate an information filtering method based on steepest descent induction algorithm combined with a two-level preference relation on user ranking. The performance of the proposed algorithm is experimentally evaluated. The ... (Update)
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BibTeX entry: (Update)
@inproceedings{ alsaffar00optimal,
author = "Ali H. Alsaffar and Jitender S. Deogun and Hayri Sever",
title = "Optimal Queries in Information Filtering",
booktitle = "International Syposium on Methodologies for Intelligent Systems",
pages = "435-443",
year = "2000",
url = "citeseer.ist.psu.edu/297723.html" }
Citations (may not include all citations):120 Inductive learning algorithms and representations for text c.. (context) - Dumais, Platt et al. - 1998
57 A comparison of classifiers and document representations for.. - Schutze, Hull et al. - 1995
41 Automated learning of decision rules for text categorization (context) - Apt, Damerau et al. - 1994
25 Evaluating text categorization - David - 1991
24 and Retrieval of Information by Computer (context) - Salton - 1988
9 A general mathematical models for information retrieval syst.. (context) - Bookstein, Cooper - 1976
8 Adaptive linear information retrieval models (context) - Bollman, Wong - 1987
8 the reuse of past optimal queries - Raghavan, Sever - 1995
7 Query formulation in linear retrieval models (context) - Wong, Yao - 1990
7 ectiveness based on user preference of documents (context) - Wong, retrieval - 1995
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