Machine Learning in Information Access
Papers from the 1996 AAAI Spring Symposium
Marti A. Hearst and Haym Hirsh, Program Cochairs
Technical Report SS-96-05. Published by The AAAI Press, Menlo Park, California. This technical report is also available in book and CD format.
Please Note: Abstracts are linked to individual titles, and will appear in a separate browser window. Full-text versions of the papers are linked to the abstract text. Access to full text may be restricted to AAAI members. PDF file sizes may be large!
Contents
Full Papers
RAVE Reviews: Acquiring Relevance Assessments From Multiple Users / 1
Richard K. Belew (UCSD) and John Hatton (Summer Institute of Linguistics)
Representational Issues in Machine learning of User Profiles / 9
Eric Bloedorn, Inderjeet Mani. and T. Richard MacMillan (MITRE)
Learning Rules that Classify E-mail / 18
William W. Cohen (AT&T Laboratories)
Combining Evidence For Effective Information Filtering / 26
Susan T. Dumais (Bellcore)
Experience with Learning Agents Which Manage Internet-Based Information / 31
Peter Edwards, David Bayer, Claire L. Green, and Terry R. Payne (University of Aberdeen)
A Grammar Inference Algorithm for the World Wide Web / 41
Terrance Goan (Stottler Henke Assoc.), Nels Belson, and Oren Etzioni (University of Washington)
Document Routing as Statistical Classification / 49
David Hull (Rank Xerox), Jan Pedersen, and Hinrich Schutze (Xerox PARC)
SIGMA: Integrating Learning Techniques in Computational Markets for Information Filtering / 54
Grigoris J. Karakoulas (Canadian Imperial Bank) Innes A. Ferguson (National Research Council, Canada)
A Framework for Comparing Text Categorization Approaches / 61
Isabelle Moulinier (Universite Paris)
Syskill & Webert: Identifying Interesting Web Sites / 69
Michael Pazzani, Jack Muramatsu, and Daniel Billsus (UC Irvine)
Applying the Multiple Cause Mixture Model to Text Categorization / 78
Mehran Sahami (Stanford), Marti Hearst, and Eric Saund (Xerox PARC)
Sampling Strategies and Learning Efficiency in Text Categorization / 88
Yiming Yang (Mayo Clinic)
Poster Papers
Multi-Media Fusion Through Application of Machine Learning and NLP / 96
Chinatso Aone, Scott William Bennett, and Jim Gorlinsky (SRA)
Improving FAQfinder’s Performance: Setting Parameters by Genetic Programming / 99
Edwin Cooper (University of Chicago)
Neural Net Learning Issues in Classification of Free Text Documents / 101
Venu Dasigi (Sacred Heart University) and Reinhold C. Mann (Oak Ridge National Laboratory)
Automatic Concept Acquisition from Real-World Texts / 104
Udo Hahn, Manfred Klenner, and Klemens Schnattinger (Freiberg University, Germany)
Inferring What a User Is Not Interested In / 107
Robert C. Holte and John Ng Yuen Yan (University of Ottawa)
Learning User Information Interests Through the Extraction of Semantically Significant Phrases / 110
Bruce Krulwich and Chad Burkey (Andersen Consulting LLP)
The Use of Active Learning in Text Categorization / 113
Ray Liere and Prasad Tadepalli (Oregon State University)
Learning Text Filtering Preferences / 116
Anadeep S. Pannu and Katia Sycara (CMU)
Do I Care? -- Tell Me What’s Changed on the Web / 119
Brian Starr. Mark S. Ackerman, and Michael Pazzani (UC Irvine)
Learning Models for Multi-Source Integration / 122
Sheila Tejada, Craig A. Knoblock, and Steven Minton (USC/ISI)
Text Classification in USENET Newsgroups: A Progress Report / 125
Scott A. Weiss, Simon Kasif. and Eric Brill (Johns Hopkins University)
AAAI Digital Library
AAAI relies on your generous support through membership and donations. If you find these resources useful, we would be grateful for your support.