AAAI-98 Workshop on Learning Text Categorization Program
AAAI-98 Workshop on Learning for Text Categorization
New!
A detailed
schedule for the workshop is available (in PostScript).
Invited Talks
- Event Tracking via Supervised and Unsupervised Learning.
Jaime Carbonell (Carnegie Mellon University)
- Finite State Revisited.
Fernando C. N. Pereira (AT&T Labs - Research)
Full Paper Presentations
- Style-based Text Categorization: What Newspaper Am I
Reading?
Shlomo Argamon-Engelson, Moshe Koppel and Galit Avneri
(Bar-Ilan Univ.)
- A Case Study in Using Linguistic Phrases for text
categorization on the WWW.
Johannes Fuernkranz, Tom Mitchell (Carnegie Mellon Univ.) and Ellen Riloff (Univ. of Utah)
- Automated Concept Extraction from Plain Text.
Boris Gelfand, Marilyn Wulfekuler and William F. Punch III (Michigan State Univ.)
- A Redundant Covering Algorithm Applied to Text
Classification.
David Hsu, Oren Etzioni and Stephen Soderland (Univ. of Washington)
- Learning Complex Patterns for Document Categorization.
Markus Junker and Andreas Abecker (German Research Center for AI)
- Adaptive Information Filtering: Learning in the Presence of
Concept Drifts.
Ralf Klinkenberg (Universitaet Dortmund) and Ingrid Renz (Daimler-Benz)
- A Comparison of Event Models for Naive
Bayes Text Classification.
Andrew McCallum (Just Research) and Kamal Nigam (Carnegie Mellon Univ.)
- Book Recommending Using Text Categorization with Extracted
Information.
Raymond J. Mooney, Paul N. Bennett and Loriene Roy (Univ. of Texas, Austin)
- A Bayesian Approach to Filtering Junk E-Mail.
Mehran Sahami (Stanford Univ.), Susan Dumais, David Heckerman and Eric Horvitz (Microsoft Research)
- Intelligent Agents for Web-based Tasks: An Advice-Taking
Approach.
Jude Shavlik and Tina Eliassi-Rad (Univ. of Wisconsin, Madison)
Poster Spotlights
- How Machine Learning Can Be Beneficial for Textual Case-Based Reasoning.
Stefanie Brueninghaus and Kevin D. Ashley (Univ. of Pittsburgh)
- Learning for Question Answering and Text Classification: Integrating Knowledge-Based and Statistical Techniques .
Jay Budzik and Kristian J. Hammond (Univ. of Chicago)
- Classifying Text Documents using Modular Categories and
Linguistically Motivated Indicators.
Eleazar Eskin and Matt Bogosian (Columbia Univ.)
- Learning Preference Relations for Information Retrieval.
Ralf Herbirch, Thore Graepel, Peter Bollmann-Sdorra and Klaus Obermayer (Technical Univ. of Berlin)
- Some Issues in the Automatic Classification of U.S.
Patents.
Leah S. Larkey (Univ. of Massachusetts, Amherst)
- Active Learning with Committees in Text Categorization:
Preliminary Results in Comparing Winnow and Perceptron.
Ray Liere and Prasad Tadepalli (Oregon State Univ.)
- SpamCop: A Spam Classification & Organization Program.
Patrick Pantel and Dekang Lin (Univ. of Manitoba)
- A Multi-Agent System for Generating a Personalized Newspaper
Digest.
Georg Veltmann (Daimler-Benz)