The dramatic growth in the number and size of on-line textual information sources has fueled increasing research interest in the information extraction (IE) problem. Given a set of text documents from some domain, an IE system automatically populates a pre-defined database by extracting relevant fragments from the documents. Manually constructed IE systems cannot adapt to domain changes, and must be adapted for each new problem domain. In consequence, various machine learning (ML) techniques---symbolic learning, inductive logic programming, wrapper induction, statistical methods, and grammar induction---have recently been applied to the IE problem. This research has led to IE systems for several genres---newswire articles, medical texts, Web pages, and Usenet posts---that automatically learn to perform IE.

The purpose of this workshop is to provide a forum for exploring the commonality underlying this diversity of problem domains and approaches. The workshop has three goals:

• to bring together communities of researchers that address the IE problem from different perspectives (e.g., the use of natural language processing for IE from grammatical text vs. extraction from semistructured documents in the context of the information integration problem);
• to deepen the IE community's understanding of the state of the art; and
• to identify remaining IE-related problems for which ML techniques might be appropriate.

TOPICS appropriate to this workshop include:

• novel or improved ML techniques for IE;
• novel types of IE domains;
• extraction from structured and semi-structured documents;
• effective use of features such as linguistic structure, mark-up, and document formatting; and
• metrics and benchmarks for evaluating IE systems.

FORMAT: In the interest of promoting as much discussion as possible, the number of paper presentations will be limited in favor of panels, invited talks, and posters. Attendance is limited to 40 participants.

Information for the authors:

Workshop Program

IMPORTANT DATES

ORGANIZING COMMITTEE

Mary-Elaine Califf Applied Computer Science Campus Box 5150 Illinois State University Normal, IL 61790-5150 - USA email: mecalif@mail.ilstu.edu phone: +1 309-438-5203 fax: +1 309-438-5113	Dayne Freitag School of Computer Science Carnegie Mellon University 5000 Forbes Avenue Pittsburgh, PA 15213 - USA email: dayne@cs.cmu.edu phone: +1 412-268-3052 fax: +1 412-268-5576
Nicholas Kushmerick Department of Computer Science University College Dublin Dublin 4 - IRELAND email: nick@ucd.ie phone: +353 1-706-2479 fax: +353 1-269-7262	Ion Muslea Information Sciences Institute / USC 4676 Admiralty Way Marina del Rey, CA 90292-6695 - USA email: muslea@isi.edu phone: +1 310-822-1511 x787 fax: +1 310-822-0751

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