10.281, Calls: American Dialect Society, Text Mining Workshop

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LINGUIST List:  Vol-10-281. Sun Feb 21 1999. ISSN: 1068-4875.

Subject: 10.281, Calls: American Dialect Society, Text Mining Workshop

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=================================Directory=================================

1)
Date:  Fri, 19 Feb 1999 12:11:45 -0500
From:  beth lee simon <simon at home2.mysolution.com>
Subject:  American Dialect Society

2)
Date:  Sat, 20 Feb 1999 21:18:54 +0200
From:  "Ronen Feldman" <ronen at instinct-soft.com>
Subject:  Text Mining Workshop/IJCAI'99

-------------------------------- Message 1 -------------------------------

Date:  Fri, 19 Feb 1999 12:11:45 -0500
From:  beth lee simon <simon at home2.mysolution.com>
Subject:  American Dialect Society

CALL FOR PROPOSALS AND ABSTRACTS

     for the 1999 American Dialect Society session of the
     Midwest Modern Language Association meeting
     November 4-6, 1999, Minneapolis, MN

     Submit 100-200 word abstracts for presentations at the
     American Dialect Society session. Open Topic.

     Abstracts will be accepted
     by email: simon at ipfw.edu

     by fax: 219-481-6985

     or by mail:
     Professor Beth Simon
     Dept of English & Linguistics
     IPFW
     Fort Wayne, IN 46805


     Cordially,

     Beth Simon
     Assistant Professor, Linguistics and English
     simon at ipfw.edu


-------------------------------- Message 2 -------------------------------

Date:  Sat, 20 Feb 1999 21:18:54 +0200
From:  "Ronen Feldman" <ronen at instinct-soft.com>
Subject:  Text Mining Workshop/IJCAI'99

	International Joint Conference on Artficial Intelligence
		TEXT MINING: FOUNDATIONS, TECHNIQUES AND APPLICATIONS
				Stockholm, Sweden
				August 2, 1999

The information age has made it easy to store large amounts of data.The
proliferation of documents available on the Web, on corporate intranets, on
news wires, and elsewhere is overwhelming. However, while the amount of data
available to us is constantly increasing, ourability to absorb and process
this information remains constant.Search engines only exacerbate the problem
by making more and more documents available in a matter of a few key
strokes; so-called "push" technology makes the problem even worse by
constantly reminding us that we are failing to follow critical news, events,
and trends. We experience information overload, missing important patterns
even as they unfold before us.

Text Mining is a new and exciting research area that tries to solve the
information overload problem by using techniques from data mining, machine
learning, information retrieval, natural-language understanding, case-based
reasoning, statistics, and knowledge management to help people gain insight
into large quantities of semi-structured or unstructured text. Text Mining
typically involves preprocessing of a document collection (such as through
text categorization or term extraction), storage and indexing of the
intermediate representations, analysis of the intermediate representations
(such as via distribution analysis, document clustering, trend analysis, and
association rule discovery), and visualization of the results. Sample topics
appropriate for this workshop include the development of efficient
algorithms for very large document collections, tools for visualizing such
document collections, the use of intelligent agents to perform text mining
on the internet, and the use information extraction to better capture the
major themes of the documents. More generally, we solicit papers in all
areas relevant to the problem of gaining insight into large collections of
text, including, but not limited to, the following areas:

Association Rule Discovery from Document Collections
Document Representations
Information Extraction for Text Mining
Multi-lingual Text Mining
Storage Issues
Taxonomy Generation for Text Mining
Term Extraction
Text Categorization
Text Mining Applications
Text Mining on the Internet
Trend Analysis
Visualization Techniques

Workshop presentations will be selected from among those submitting a ten-to
twelve-page paper on their work. Papers should be in postscript, PDF, HTML,
or plain text format, and should be submitted by emailing a URL to
feldman at cs.biu.ac.il that points to the submission. (Those for whom doing so
would be a hardship should contact feldman at cs.biu.ac.il to arrange an
alternative submission method.) Those wishing to attend without making a
presentation should instead email feldman at cs.biu.ac.il a short (at most one
page) summary of their interests. We also plan to have a demo session for
research and commercial text mining systems, and those wishing to
participate in this session should email feldman at cs.biu.ac.il a one-page
description of their system/demo.


Submission Deadline: April 15th 1999
Accept/Reject Answers mailed: May 5th 1999
Deadline for receipt of camera-ready copy: May 15th 1999


Program Committee
Rakesh Agrawal (IBM, Almaden, USA)
Yonatan Aumann (Bar-Ilan University and Instinct Software, ISRAEL)
Ronen Feldman, Co-Chair (Bar-Ilan University and Instinct Software,ISRAEL)
Marti Hearst, (UC Berkeley, USA)
Haym Hirsh, Co-Chair (Rutgers, USA)
Willi Kloesgen (GMD, Germany)
Yves Kodratoff (LRI, France)
Heikki Mannila (Microsoft Research, USA)
Martin Rajman (EPFL, Switzerland)
Ian Witten, (New Zealand)



Send submissions to
Ronen Feldman
Director, Data Mining Laboratory
Department of Mathematics and Computer Science
Bar-Ilan University
Ramat-Gan, ISRAEL, 52900
(972) 3-5318629 (tel)
(972) 3-5353325 (fax)
Email: feldman at cs.biu.ac.il

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