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PKDD'2000 Workshop :
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MACHINE LEARNING AND TEXTUAL INFORMATION ACCESS
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September 12, 2000.
Lyon, France.
Preceding the Fourth European Conference on Principles and
Practices of Knowledge Discovery in Databases (PKDD'2000).
PKDD'200 : http://eric.univ-lyon2.fr/~pkdd2000/
WORKSHOP : http://www-connex.lip6.fr/mltia2000.htlm
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CALL FOR PAPERS
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DESCRIPTION:
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Until recently, the exploitation of large textual collections was mainly
limited to sorting and retrieving documents. On the other hand, systems
capable of extracting meaningful document fragments dealt only with
small
domain dependent tasks and models.
On-line information is becoming widely available and utilized, and
demand
for tools capable of harnessing this information increases rapidly. As
this information is inherently structured and complex, classic models
are
insufficient. New technological challenges arise, the solution of which
require the cooperation of several research domains.
By the term "Textual Information Access" we denote here an emerging
interdisciplinary community of researchers from different fields sharing
an interest on textual data objects, and Machine or Statistical Learning
techniques to develop automatic text analysis systems.
Among the new important challenges we will mention the need for
automatically
parametrizable systems (since hand-crafted models cannot cope with the
heterogeneous nature of data and tasks), the exploitation of new
structure
formalisms for documents and collections (e.g. XML), the relations
between
textual and not textual data, and more generally the emerging
text-mining
and web-mining tasks. In order to solve these challenges, a combined
approach is needed, exploiting technologies from different domains.
TOPICS OF RELEVANCE:
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Textual Information Access models and applications relating to:
Information Retrieval and Filtering
Information Extraction
Multi-media Information Access
Knowledge Acquisition
Topic Detection and Tracking
Text Summarization
Representation techniques of:
Textual Information
Structure
Semantics
User-feedback models and applications
User-modeling models and applications
Clustering methods and applications
Large corpus, scalability and performance issues
Evaluation techniques
SOLICITED CONTRIBUTIONS
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Long papers (up to 12 pages), reporting original completed research,
development activities, original state of the art surveys, etc.
Short papers (from 4 to 6 pages), reporting ongoing research, promising
new approaches, position papers.
All papers will be peer reviewed. Accepted papers will presented during
the Workshop and will appear in the Workshop Proceedings.
ORGANIZING COMMITTEE
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Jean-Cédric Chappelier, EPFL, Switzerland,
Robert Gaizauskas, University of Sheffield, UK,
Patrick Gallinari, LIP6, Université de Paris 6, France,
Thorsten Joachims, Universitaet Dortmun, Germany,
Martin Rajman, EPFL, Switzerland,
Hugo Zaragoza, Université de Paris 6, France (Chairman).
SUBMISSION
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Submissions should include a short abstract (200 words) and comply with
the following format: A4, 1 column, 2.5cm margins, Times New Roman
12point
font, single spacing. Postscript is preferred but other standard formats
will be accepted (Word, latex, etc.)
Submissions should be done electronically by e-mail to Hugo Zaragoza
(Hugo.Zaragoza@lip6.fr), indicating in the subject: MLTIA'2000.
Please notify to us your intention to submit as soon as possible.
IMPORTANT DATES
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June 25th 2000 : Deadline for electronic submission of all papers.
August 1st 2000 : Notification of acceptance.
August 15th 2000 : Deadline for electronic submission of camera-ready
paper.
Contact Details
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For more information, please contact:
Hugo Zaragoza
LIP6, Université Pierre et Marie Curie (Paris 6)
4, place Jussieu #169
75252 Paris Cedex 05
France.
Tel: 33 1 44 27 74 91
Fax: 33 1 44 27 70 00
Email: Hugo.Zaragoza@lip6.fr
--
Hugo Zaragoza.
Machine Learning Group Tel: (33/0) 1 44277491
LIP6, Univeristé de Paris 6 Fax: (33/0) 1 44277000
Paris (France) Hugo.Zaragoza@lip6.fr
http://www-poleia.lip6.fr/~zaragoza
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LIP6 / UPMC, Boite 169 / 4, pl.Jussieu / 75252 Paris Cedex 05
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