Workshop on
"Machine Learning for Information Filtering"
at IJCAI 99
August 1st, 1998
Stockholm, Sweden
http://www-ai.cs.uni-dortmund.de/EVENTS/IJCAI99-MLIF
The enormous growth of on-line information and electronic commerce has
brought about a comparable growth in research on methods for
automatically organizing and personalizing information. The
"information filtering" task has simultaneously emerged as an active
research topic in several disciplines, including information retrieval,
human computer interaction, natural language processing, and machine
learning. The information filtering task manifests itself in many
theoretically challenging and commercially important applications, such
as electronic commerce and marketing, search engines, information push
applications, browsing assistants, and adaptive Web sites.
The goal of this workshop is to bring together researchers working on
information filtering from many subfields of AI, while emphasizing the
machine learning techniques and algorithms many of these subfields
share. These techniques include
* text classification methods (probabilistic methods, support vector
machines, first order methods, use of unlabeled data, etc.)
* collaborative filtering methods (use of complex user and object
profiles (e.g. citation structure), novel clustering models and
methods, etc.)
* other methods for learning user preferences (learning orderings,
etc.)
* combinations of approaches and multi-strategy learning
* representational issues (knowledge representation, NLP techniques,
representing interest, representing information objects, feature
selection, term weighting, data transformation, latent semantic
indexing, etc.)
* clustering methods (similarity measures, mixture models, etc.)
* scalability issues
* formal models and theory
* handling different media (text, images, sound, etc.)
* evaluation techniques
Besides these topics, the workshop covers all theoretical and
methodological issues concerning information filtering. Submissions
describing innovative applications of information filtering are also
encouraged. By bringing together industrial representatives with
researchers, the workshop will
* show how problems from industry present new research issues.
* identify ways in which research results may be put in more
widespread practice in an industrial setting.
TIMETABLE
April 6, 1999 Submission deadline
May 3, 1999 Notification of acceptance
May 24, 1999 Camera-ready copy due
August 1, 1999 Workshop
ORGANIZATION
The workshop will be one full day, including invited talks, paper
presentations, poster presentations, and numerous opportunities for
discussion. Depending on submissions, there will be joint sessions with
the workshop "Text Mining: Foundations, Techniques and Applications" on
topics of common interest. Participation in the workshop is limited
according to IJCAI regulations. All workshop participants have to
register for the IJCAI conference. The working notes of the workshop
will be published online.
SUBMISSION PROCEDURE
Those interested in making a presentation should submit a full paper
electronically either as a Postscript or PDF to
joachims@ls8.cs.uni-dortmund.de. The first page of submitted papers
should include: title, author names and affiliations, a brief abstract.
It should also name a designated contact person with his or her postal
address, electronic mail address, telephone and fax number.
Submissions
should not exceed 8 pages according to the IJCAI formatting
instructions
and should be printable on 8.5" x 11" or A4 paper.
Those interested in participating in the workshop, but not submitting a
paper, should submit a one-page abstract of their research interests in
learning methods for information filtering.
ORGANIZING COMMITTEE
Thorsten Joachims (Chair) Andrew McCallum
Universitaet Dortmund Just Research
FB Informatik, LS8 4616 Henry Street
Baroper Str. 301 Pittsburgh, PA 15213
44221 Dortmund, Germany Phone: (412) 683-9132
Phone: +49 231 755 5102 FAX: (412) 683-4175
FAX: +49 231 755 5105 Email: mccallum@justresearch.com
joachims@ls8.cs.uni-dortmund.de
Mehran Sahami Lyle Ungar
Epiphany, Inc. University of Pennsylvania
2300 Geng Road Dept of Comp. and Info. Sci.
Palo Alto, CA 94303 200 S. 33rd St.
Phone: (650) 496-2399 Philadelphia, PA 19104-6389
FAX: (650) 496-2431 Phone: (215) 898-7449
Email: sahami@epiphany.com FAX: (215) 898-0587
Email: ungar@cis.upenn.edu
FURTHER INFORMATION
http://www-ai.cs.uni-dortmund.de/EVENTS/IJCAI99-MLIF