KDD Nuggets 95:26, e-mailed 95-10-20 Contents: * GPS, New book: Elements of Machine Learning by Pat Langley http://Market.NET/literary/mkp/pages/3018/index.html * Jeffrey C. Schlimmer, ICML-96: Final Call for Papers http://www.di.unito.it/pub/WWW/ICML96/main.html * J. Han, IEEE TKDE Special Issue on Data Mining * G. Melli, Synthetic Classification Data Sets (SCDS) program, http://fas.sfu.ca/cs/people/GradStudents/melli/SCDS -- The KDD Nuggets is a moderated mailing list on Data Mining and Knowledge Discovery in Databases (KDD). Please include a DESCRIPTIVE subject line and a URL, when available, in your submission. Nuggets frequency is approximately weekly. Back issues of Nuggets, a catalog of S*i*ftware (data mining tools), references, and other related information is available at Knowledge Discovery Mine, URL http://info.gte.com/~kdd or anonymous ftp to ftp.gte.com, cd /pub/kdd, get README (however ftp site is generally less up to date). E-mail add/delete requests to kdd-request@gte.com E-mail contributions to kdd@gte.com -- Gregory Piatetsky-Shapiro (moderator) ********************* Official disclaimer *********************************** * All opinions expressed herein are those of the writers (or the moderator) * * and not necessarily of their respective employers (or GTE Laboratories) * ***************************************************************************** ~~~~~~~~~~~~ Quotable Quote ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Always seek simplicity, and distrust it. Roger Taylor (thanks to Ken Laws TCC List) >~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ From: mkp@mkp.com (Morgan Kaufmann) Newsgroups: comp.ai,comp.ai.edu,comp.edu,misc.books.technical Subject: New Book: Elements of Machine Learning Date: Wed, 11 Oct 1995 11:12:16 Organization: Morgan Kaufmann Publishers Keywords: book,learning,algorithm Produced in cooperation with the Institute for the Study of Learning and Expertise, Pat Langley's new book, Elements of Machine Learning, illustrates a variety of basic algorithms for inducing simple concepts from experience, presents alternatives for organizing learned concepts into large-scale structures, and discusses adaptations of the learning methods to more complex problem-solving tasks. The chapters describe these computational techniques in detail and give examples of their operation, along with exercises and references to the literature. ISBN 1-55860-310-8; hardcover; 419 pages. For more information contact Morgan Kaufmann Publishers email: mkp@mkp.com www: http://mkp.com phone: 800-745-7323 / 415-392-2665 fax: 415-982-2665 >~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ From: "Jeffrey C. Schlimmer" Subject: ICML-96: Final Call for Papers To: ml95@eecs.wsu.edu Date: Fri, 13 Oct 1995 12:05:38 -0700 (PDT) ************************************************** ICML'96 13th International Conference on Machine Learning Bari (Italy), July 3-6th, 1996 ************************************************** Call for Papers and Workshop Proposals ************************************************** General Information ------------------- The 13th International Conference on Machine Learning (ICML'96) will be held in Bari, Italy, during July 3-6th, 1996, with informal workshops on July 3rd. The purpose of the conference is twofold: firstly, to emphasize the potential of machine learning approaches for solving problems in a wide range of application domains, secondly, to highlight relationships between machine learning and other fields, such as statistics, pattern recognition, artificial intelligence, information retrieval, instructional and cognitive sciences, software engineering. In order to stress the multidisciplinary character of the field and the large spectrum of possible application domains, the Program Committe has been widened to include also experts from fields related to or interested in Machine Learning. The Conference on Computational Learning Theory (COLT'96) will be also held in Italy, namely in Desenzano sul Garda, on June 28th-July 1st, 1996. Program ------- The scientific program will include invited talks, presentations of refereed papers and a session of general discussion. Submissions are invited in all areas of Machine Learning, including, but not limited to: Abduction Analogy Applications of machine learning Artificial neural networks Case-Based learning Cognitive models of learning Computational learning theory Explanation-based learning Formal models of learning Inductive learning Inductive logic programming Genetic algorithms Knowledge discovery in databases Learning and problem solving Multistrategy learning Reinforcement learning Representation change Scientific discovery Theory revision Paper Format ------------ Submissions must be clearly legible, with good quality print. Papers are limited to twelve (12) pages, excluding title page and bibliography, but including all tables and figures. Papers must be printed on 8-1/2 x 11 inch paper or A4 format, using 12 point type (10 characters per inch), with no more than 40 lines per page. A separate title page must include the title of the paper, the email and postal addresses of all authors, up to three keywords, and a clear summary of the main contributions of the paper. The title page of accepted papers will be made available via World-Wide Web before the conference take place. Double-sided printing in encouraged. Requirement for Submissions --------------------------- Please send five (5) copies of each submitted paper to the Program Chair. Submissions must be received by January 21st, 1996. Electronic or Fax submissions are not acceptable. Notification of acceptance or rejection will be mailed to the first (or designated) author by March 8th 1996. Camera-ready accepted papers are due on April 6th, 1996. Review Criteria --------------- Each submitted paper will be reviewed by three members of the Program or Advisory Committee, and will be judged on significance, originality and clarity. Papers addressing application issues are welcome. Simultaneous submission to other conferences must be explicitly declared. In the case of multiple acceptance, presentation at ICML'96 and inclusion in the proceedings is only granted upon withdrawal from the other conference(s). Workshop Proposals ------------------ Workshop proposals are invited in all areas of Machine Learning. Please send a two (2) page description of the proposed workshop, its objectives, organizer(s), and expected number of attendees. The proposal must be received by the Workshop Chair by December 15th, 1995. Descriptions of accepted workshops will be made available via World-Wide Web. Notification of acceptance or rejection will be mailed to the organizer by January 31st, 1996. Calls for Papers for accepted workshops will be responsibility of the organizer(s). Program Chair ------------- Lorenza Saitta saitta@di.unito.it Universita di Torino Phone: (+39) 11 - 7429.214 Dipartimento di Informatica Fax: (+39) 11 - 751.603 Corso Svizzera 185 10149 Torino (Italy) Local Chair ----------- Floriana Esposito esposito@vm.csata.it Universita di Bari Phone: (+39) 80 - 5443.264 Dipartimento di Informatica Fax: (+39) 80 - 5443.196 Via Orabona 4 70125 Bari (Italy) Workshop Chair -------------- Stefan Wrobel (wrobel@gmdzi.gmd.de) GMD, FIT.KI Schlo Birlinghoven 53754 Sankt Augustin (Germany) Publicity Chair --------------- Jeff Schlimmer (schlimme@eecs.wsu.edu) School of Electrical Engineering and Computer Science Washington State University Pullman, WA 99164-2752 (USA) Wolfgang Banzhaf (University of Dortmund, Ge smap (V1.3) Advisory Committee ------------------ Jaime Carbonell (Carnegie Mellon University, USA) William Cohen (AT&T Bell Laboratories, USA) Kenneth De Jong (George Mason University, USA) Tom Dietterich (Oregon State University, USA) Tom Mitchell (Carnegie Mellon University, USA) Stuart Russell (University of California at Berkeley, USA) Derek Sleeman (University of Aberdeen, UK) Paul Utgoff (University of Massachusetts, USA) Program Committee ----------------- Naoki Abe (C&C Research Laboratory, Japan) Christopher Atkeson (Georgia Tech, USA) Wolfgang Banzhaf (University of Dortmund, Germany) Andrew Barto (University of Massachusetts, USA) Francesco Bergadano (Universita di Torino, Italy) Ivan Bratko (University of Ljubljana, Slovenia) Carla Brodley (Purdue University, USA) Jason Catlett (AT&T Bell Laboratories, USA) Eugene Charniak (Brown University, USA) Bruce Croft (University of Massachusetts, USA) Peter Dayan (MIT, USA) Gerald DeJong (University of Illinois at Urbana, USA) Luc De Raedt (Katholieke Universiteit Leuven, Belgium) Yves Deville (Universite Catholique de Louvain, Belgium) Charles Elkan (University of California at San Diego, USA) Tom Ellman (Rutgers University, USA) Usama Fayyad (California Institute of Technology, USA) Nick Flann (Utah State University, USA) Paolo Fortina (Children's Hospital of Philadelphia, USA) John Grefenstette (Naval Research Laboratory, USA) Russell Greiner (Siemens Corporate Research, USA) David Hand (The Open University, UK) Michael Jordan (MIT, USA) Leslie Kaelbling (Brown University, USA) Yves Kodratoff (Universitee de Paris-Sud, France) Kurt Konolige (SRI International, USA) Wolfgang Maass (Teknische Universitat Graz, Austria) David MacKay (Cavendish Laboratory, UK) Donato Malerba (Universita di Bari, Italy) Chris Matheus (GTE Laboratories, USA) Ray Mooney (University of Texas, USA) Katharina Morik (University of Dortmund, Germany) Hiroshi Motoda (Hitachi Ltd., Japan) Michael Pazzani (University of California at Irvine, USA) Daryl Pregibon (AT&T Bell Laboratories, USA) Armand Prieditis (University of California at Davis, USA) Peter Reimann (University of Freiburg, Germany) Claude Sammut (University of New South Wales, Australia) Robert Schapire (AT&T Bell Laboratories, USA) Devika Subramanian (Rice University, USA) Prasad Tadepalli (Oregon State University, USA) Sebastian Thrun (Carnegie Mellon University, USA) Naftali Tishby (The Hebrew University, Israel) Raul Valdes-Perez (Carnegie Mellon University, USA) Vladimir Vapnik (AT&T Bell Laboratories, USA) Manuela Veloso (Carnegie Mellon University, USA) Organizing Committee -------------------- Giovanni Semeraro (Italy) semeraro@vm.csata.it Marco Botta and Filippo Neri (Italy) {botta, neri}@di.unito.it General Inquiries ----------------- Please address general inquiries to any of the members of the Organizing Committee or to the address: icml96@di.unito.it ICML'96 has its own page on the World-Wide Web in the URL at: http://www.di.unito.it/pub/WWW/ICML96/home.html This announcement is also available in PostScript in the URL at: ftp://ftp.di.unito.it/pub/ICML96/callforpapers.ps In order to be included in the mailing list, please send a note to the Publicity Chair. Important dates ---------------- Workshop submission deadline: December 15, 1995 Paper submission deadline: January 21, 1996 Notification of workshop acceptance: January 31, 1996 Notification of paper acceptance: March 8, 1996 Camera-ready copy: April 6, 1996 >~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ From: han@cs.sfu.ca Date: Fri, 13 Oct 95 19:31:57 PDT Subject: CFP: IEEE TR. on Knowledge and Data Eng. -- Issue on Data Mining CALL FOR PAPERS Special Issue on Database Mining IEEE Trans. on Knowledge and Data Engineering Mining information and knowledge from large databases has been recognized by many researchers as a key research topic in database systems and machine learning, and by many industrial companies as an important area with an opportunity of major revenues. Researchers in many different fields, including database systems, knowledge-base systems, artificial intelligence, machine learning, knowledge acquisition, statistics, spatial databases, and data visualization, have shown great interest in database mining. Furthermore, several emerging applications in information providing services, such as on-line services and World Wide Web, also call for various data mining techniques to better understand user behavior, to meliorate the service provided, and to increase the business opportunities. A special issue of IEEE Transactions on Knowledge and Data Engineering will be devoted to this topic. Areas of interest include, but not limited to, the following: Principles of Data Mining and Knowledge Discovery Tools, Techniques, and Performance Improvements for Database Mining Data Representation, Knowledge Visualization and Interactive Database Mining Parallel and Distributed Algorithms for Database Mining Integration of Different Database Mining Capabilities and Methods Knowledge Discovery in Spatial, Temporal, and Heterogeneous Databases Knowledge Discovery Systems and Implementations Database Mining Applications Instructions for Submitting Papers Manuscript should be no more than 25 typewritten pages with a 12-point font and double spacing, including figures and references. Papers must not have been published previously or currently submitted for publication elsewhere. Each manuscript should have a title page with the title of the paper, full name(s) and affiliation(s) of author(s), complete postal and electronic addresses, telephone number(s), a FAX number, an informative 150-200 words abstract, and a list of identifying keywords. Send six copies of each submission to one of the guest editors. For further information, contact the guest editors. Important Dates Manuscript due: Feb. 1, 1996 Acceptance Notification: May 15, 1996 Final manuscript due: July 1, 1996 Publication date of issue: Dec. 1996 Guest Editors: Philip S. Yu, Ming-Syan Chen, and Jiawei Han Dr. Philip S. Yu IBM Thomas J. Watson Research Ctr. P.O. Box 704 Yorktown Heights, NY 10598 Tel: (914) 784-7141 email: psyu@watson.ibm.com Dr. Ming-Syan Chen IBM Thomas J. Watson Research Ctr. P.O. Box 704 Yorktown Heights, NY 10598 Tel: (914) 784-7517 email: mschen@watson.ibm.com Prof. Jiawei Han School of Computing Science Simon Fraser University B.C., Canada V5A 1S6 Tel: (604) 291-4411 email: han@cs.sfu.ca >~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Date: Fri, 20 Oct 1995 10:32:43 -0400 From: Gabor Melli (melli@cs.sfu.ca) Subject: Synthetic Classification Data Sets (SCDS) program One important way to test learning-from-example algorithms is to test against well understood synthetic data sets. The Synthetic Classification Data Sets (SCDS) program [URL http://fas.sfu.ca/cs/people/GradStudents/melli/SCDS] has been created to generate synthetic data sets which are particularly useful to test Knowledge Discovery from Database (KDD) algorithms. SCDS generates a customizable conjunctive normal form rule base which is then used to generate synthetic data sets. These data sets can also be customized to include some real-world characteristics such as irrelevant attributes, missing attributes, noisy data and missing values. While the ANSI C code for version 1.2 is available, you may want to first try out the user- friendly interactive WWW Form interface. The page http://fas.sfu.ca/cs/people/GradStudents/melli/SCDS contains: Overview of classification, KDD, and synthetic data sets. Information about configurable SCDS parameters Create some Synthetic Data Interactively on a WWW HTML Form Simple example Intermediate example Complex example C source code and Makefile. Makefile v1.2 Source (scds.c) Things to do and ongoing questions. >~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~