pkarp@NCBI.NLM.NIH.GOV (Peter Karp) (12/12/90)
Date: Tue, 4 Dec 90 10:57:24 -0500 From: Gregory Piatetsky-Shapiro <gps0%harvey@gte.COM> Message-Id: <9012041557.AA29517@harvey.gte.com> To: ml@ICS.UCI.EDU Subject: AAAI-91 Workshop on Knowledge Discovery in Databases - CFP Call for Papers for AAAI Workshop on KNOWLEDGE DISCOVERY IN DATABASES Anaheim, California, July 14-15 (tentative), 1991. The growing data and information glut creates both a need and an opportunity for extracting knowledge from databases. Earth observation satellites are expected to produce terabytes of data. Increasing computerization of businesses generates large databases, which some forward looking companies (airlines, banks, insurance companies, etc.) are already searching for knowledge offering competitive advantage. Several statistical and machine learning tools for discovery in databases are available commercially. Recent research progress, coupled with reported application successes, created a significant interest in KDD and led to an IJCAI-89 workshop on KDD and the Knowledge Discovery in Databases collection (AAAI/MIT Press, Spring 1991). Discovery in databases is not a strict sub-field of AI. Rather it is an area of common interest for researchers in machine learning, statistics, intelligent databases, knowledge acquisition for expert systems, and data visualization. Too often researchers in one of these areas are unaware of important tools and techniques in the other areas. A major goal of the workshop is to bring together researchers in different areas to cross-fertilize the various research approaches and discuss the unifying themes of KDD, such as the use of domain knowledge, dealing with uncertainty and imperfect data, and interactive, human-oriented presentation. This 1.5 day workshop will bring together academic and industrial researchers, business practitioners, and tool developers. Specific topics of interest include: Integration of Knowledge-based and Statistical Approaches Integration of Different Discovery Methods Use of Domain Knowledge in Discovery and Re-use of Discovered Knowledge Discovery of Causal Structure in Data Interactive Systems for Data Exploration and Discovery Human-Oriented Presentation, including Data Visualization High-level Query Answering and Data Summarization Discovery in Complex Data or Text Ethics of Discovery in Social Databases Successful Applications in Medicine, Business and other areas. Please submit 3 copies of either an extended abstract (about 5 pages), a short paper (about 10 pages), a comparative survey of existing tools and techniques, or a description of a successful application to the workshop chairman: Gregory Piatetsky-Shapiro Important Dates----------------------- GTE Laboratories, M/S 45 Submissions Due: March 8, 1991 40 Sylvan Road, Waltham, MA 02254 Acceptance Notification: April 15, 1991 e-mail: gps0@gte.com Workshop Notes due to fax: 617-890-9320 tel: 617-466-4236 AAAI (camera-ready): May 24, 1991 To encourage active discussion, workshop participation will be limited. Working notes will be produced by AAAI and distributed to participants. Organizing Committee: Tom Dietterich (Oregon State University) William (Bud) Frawley (GTE Laboratories) Brian Gaines (University of Calgary) Chris Matheus (GTE Laboratories) Mary McLeish (University of Guelph) Michael Siegel (MIT Sloan School) Samy Uthurusamy (GM Research Laboratories) Jan Zytkow (Wichita State University) ------------------------------ END of ML-LIST 2.24