CFPPrevious | item21 | NextDate: Thu, 6 Apr 2000 13:23:49 -0400 (EDT) From: Ivan Bruha bruha@mail.cas.McMaster.CA Subject: CFP: KDD-2000, workshop "Postprocessing in ML and DM" C A L L F O R P A P E R S Post-Processing in Machine Learning and Data Mining: Interpretation, Visualization, Integration, and Related Topics :::::A WORKSHOP WITHIN:::: KDD-2000: The Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining August 20-23, 2000, Boston, MA, USA http://www.acm.org/sigkdd/kdd2000 This workshop addresses an important aspect related to the Data Mining (DM) and Machine Learning (ML) in post-processing and analyzing knowledge bases induced from real world databases. Results of a genuine ML algorithm, such as a decision tree or a set of decision rules, need not be perfect from the view of custom or commercial applications. It is quite known that a concept description (knowledge base, model) discovered by an inductive process has to be usually processed by a post-pruning procedure. Most existing procedures evaluate the extracted knowledge, visualize it, or merely document it for the end user. Also, they may interpret the knowledge and incorporate it into an existing system, and check it for potential conflicts with previously derived knowledge (models). All post-processing procedures thus provide a kind of "symbolic filter" for noisy, imprecise, or "non-user-friendly" knowledge derived by an inductive algorithm. The workshop will focus on all aspects of post-processing procedures, including: o knowledge evaluation o rule quality processing and evaluation o knowledge filtering: rule truncation and postpruning o interpretation of the knowledge (models) acquired o explanation o visualization of the new knowledge o merging new knowledge with a-priori knowledge provided by a human expert o knowledge combination and integration o model refinement o model fusion o selecting the best presentation approach Thus, the post-processing tools are complementary to the DM algorithms and always help the DM algorithms to refine the acquired knowledge. Usually, these tools exploit techniques that are not genuinely logical, e.g., statistics, neural nets, and others. These reasons let us to launch this workshop. In fact, we would like to invite practical, experienced, and empirical applications. We would like to focus on industry and business applications, but we will review any functional applications of the above concern in any discipline. The theme of this workshop is directly related to applications of existing tools in KDD: 1. The workshop will provide a forum for researchers and practitioners who are interested in the scope of the workshop to exchange information by attending and/or presenting a paper. It is intended to encourage informal presentations of important problems, work in progress, or research ideas that may not have reached maturity. 2. The workshop organizers are interested in presentations from real world applications, vendors of data mining tools, specially focussing on challenges, limitations, constraints that they have faced in developing, using post-processing techniques and model fusion. 3. We have already organized within ICML-99 a workshop on pre- and post-processing. Since majority of contributions at that workshop were focused on pre-processing only, we would like to support the post-processing issue within this KDD workshop. Organizers ---------- A. (Fazel) Famili (co-chair) Ivan Bruha (co-chair) Editor-in-Chief, Intelligent Data Analysis Dept. Computing & Software Institute for Information Technology McMaster University National Research Council of Canada Hamilton, Ont Ottawa, Ont Canada L8S 4L7 Canada K1A 0R6 email: Fazel.Famili@iit.nrc.ca email: bruha@mcmaster.ca http://www.iit.nrc.ca/~fazel http://www.cas.mcmaster.ca/~bruha phone: +1-613-9938554 phone: +1-905-5259140 ext 23439 fax : +1-613-9527151 fax: +1-905-5240340 Programming Committee --------------------- Petr Berka, Laboratory of Intelligent Systems, University of Economics, Prague, Czech Republic email: berka@vse.cz , http://lisp.vse.cz/~berka Marko Bohanec, Institute Jozef Stephan, Jamova 37, Ljubljana, Slovenia email: marko.bohanec@ijs.si , http://www-ai.ijs.si/MarkoBohanec/mare.html Ivan Bruha (co-chair) A. (Fazel) Famili (co-chair) W.F.S. (Skip) Poehlman, McMaster University, Hamilton, Canada email: skip@church.cas.mcmaster.ca Organization Notes ------------------ There will be one or two invited talks on the workshop which will survey the given topic as well as introduce their own research. Each paper will be reviewed by two reviewers and up to 10 accepted papers will be presented (each 15-20 min). If there is a larger interest, then some papers might be accepted as posters. Maximum size is 10 (ten) pages. Submit your paper either by regular mail or by Email to both of the co-chairs. ^^^^^^^^^^^^^^^^^^^^^^^^ If you use Email, then please submit your paper in PostScript, format. Workshop proceedings will be published as a technical report in collaboration with the KDD-2000 organization committee. Please note that authors of the best papers will be invited to submit an extended version of their papers to the Intelligent Data Analysis Journal: see http://www.iospress.nl/html/1088467X.html for details. Schedule for paper submission ----------------------------- Deadline for paper submission: 15 May 2000 Notification of acceptance: 15 June 2000 Deadline for final camera ready papers: 15 July 2000 Previous | item21 | Next |
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