Editor for this issue: Karen Milligan <karen
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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: simonMail to author|Respond to list|Read more issues|LINGUIST home page|Top of issueipfw.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
ipfw.edu
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 feldmanMail to author|Respond to list|Read more issues|LINGUIST home page|Top of issuecs.biu.ac.il that points to the submission. (Those for whom doing so would be a hardship should contact feldman
cs.biu.ac.il to arrange an alternative submission method.) Those wishing to attend without making a presentation should instead email feldman
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
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
cs.biu.ac.il