CFP of AM-2002: Call For Paper of INTERNATIONAL WORKSHOP ON ACTIVE MINING (AM-2002) IN ICDM2002: THE 2002 IEEE INTERNATIONAL CONFERENCE ON DATA MINING Maebashi TERRSA, Maebashi City, Japan Workshop URL of ICDM2002: http://www.mathcs.sjsu.edu/faculty/tylin/icdm02_workshop.html (Main URL of ICDM2002: http://kis.maebashi-it.ac.jp/icdm02/)
Active mining is a new direction in the knowledge discovery process for real- world applications handling various kinds of data with actual user need. Our ability to collect data, be it in business, government, science, and perhaps personal, has been increasing at a dramatic rate. However, our ability to analyze and understand massive data lags far behind our ability to collect them. The value of data is no longer in "how much of it we have". Rather, the value is in how quickly and how effectively can the data be reduced, explored, manipulated and managed. Knowledge Discovery and Data mining (KDD) is an emerging technique that extracts implicit, previously unknown, and potentially useful information (or patters) from data. Recent advancement made through extensive studies and real world applications reveals that no matter how powerful computers are now or will be in the future, KDD researchers and practitioners must consider how to manage ever-growing data which is, ironically, due to the extensive use of computers and ease of data collection, ever-increasing forms of data which different applications require us to handle, and ever-changing requirements for new data and mining target as new evidences are collected and new findings are made. In short, the need is ever increasing in this era of information overload for 1) identifying and collecting the relevant data from a huge information search space, 2) mining useful knowledge from different forms of massive data efficiently and effectively, and 3) promptly reacting to situation changes and giving necessary feedback to both data collection and mining steps. Active mining is a collection of activities each solving a part of the above need, but collectively achieves the various mining need. By "collectively achieving" we mean that the total effect outperforms the simple add-sum effect that each individual effort can bring. Said differently, a spiral effect of these interleaving three steps is the target to be pursued. To achieve this goal the initial action is to explore mechanisms of 1) active information collection where necessary information is effectively searched and preprocessed, 2) user-centered active mining where various forms of information sources are effectively mined, and 3) active user reaction where the mined knowledge is easily assessed and prompt feedback is made possible. The objectives of this workshop is to gather researchers as well as practitioners who are working on various research fields of active mining, share hard-learned experiences, and shed light on future development of active mining. This workshop will address many aspects of active mining ranging from theories, methodologies, algorithms, to their applications. Through this workshop, we hope to produce a contemporary overview of modern solutions and to create synergy among different branches but with a similar goal - facilitating data collection, processing and knowledge discovery via active mining. Topics of the conference include, but are not limited to, the following areas. Discovery of new information source Active collection of information Tools for information collection Information filtering Information retrieval, collection, and integration on WWW for data mining Data mining process Inspection and validation of mined pieces of knowledge Description language for discovery Evaluation and accountability Interactive mining Design and deployment of customer response model in CRM Adaptive modeling in data mining Selection, transformation, and construction of features Selection and construction of instances Exception/deviation discovery Visualization Spatial data mining Text mining Graph mining Success/failure stories in data mining and lessons learned Data mining for evidence-based medicine Distributed data mining Data mining for knowledge management Active learning Meta learning Active sampling Usability of mined pieces of knowledge User interface for data mining The workshop will consist of the three invited talks by Saso Dzeroski (Jozef Stefan Institute, Slovenia), Luc de Raedt (University of Freiburg, Germany), Stefan Wrobel (University of Magdeburg, Germany), and presentation of contributed papers and posters. IMPORTANT DATES Deadline of Paper Submission : September, 30, 2002 Notification of Review Result: October, 15, 2002 Deadline of Camera Ready Copy; November, 4, 2002 Workshop Date : December, 9, 2002 PAPER FOR SUBMISSION The paper for the review must follow the standard IEEE-Computer Society Format (URL: http://www.computer.org/cspress/instruct.htm). The length of the paper must be within 6 pages. The paper exceeding this length will not be reviewed. The paper prepared for the review in PDF format must be attached to a mail, and sent to the following address. Address for Paper Submission: [EMAIL PROTECTED] WORKSHOP ORGANIZATION Workshop Chair : Hiroshi Motoda (Osaka University, Japan) Program Committee Chair: Takashi Washio (Osaka University, Japan) Program Committee Members: Hiroki Arimura (Kyushu University, Japan) Stephen D. Bay (Stanford University, U.S.A.) Wesley Chu (UCLA, U.S.A.) Saso Dzeroski (Jozef Stefan Institute, Slovenia) Shoji Hirano (Shimane Medical University, Japan) Tu Bao Ho (JAIST, Japan) Robert H.P. Engels (CognIT, Norway) Ryutaro Ichise (NII, Japan) Akihiro Inokuchi (IBM Japan, Japan) Hiroyuki Kawano (Kyoto University, Japan) Yasuhiko Kitamura (Osaka City University, Japan) Marzena Kryszkiewicz (Warsaw University of Technology, Poland) T.Y. Lin (San Jose State University, U.S.A.) Bing Liu (University of Illinois at Chicago, U.S.A.) Huan Liu (Arizona State University, U.S.A.) Tsuyoshi Murata (NII, Japan) Masayuki Numao (Tokyo Institute of Technology, Japan) Miho Ohsaki (Shizuoka University, Japan) Takashi Onoda (CRIPEI, Japan) Luc de Raedt (University of Freiburg, Germany) Henryk Rybinski (Warsaw University of Technology) Masashi Shimbo (NAIST, Japan) Einoshin Suzuki (Yokohama National University, Japan) Masahiro Terabe (MRI, Japan) Ljupico Todorovski (Jozef Stefan Institute, Slovenia) Seiji Yamada (NII, Japan) Yiyu Yao (University of Regina, Canada) Kenichi Yoshida (University of Tsukuba, Japan) Tetsuya Yoshida (Osaka University, Japan) Stefan Wrobel (University of Magdeburg, Germany) CONTACT PERSON Prof. Takashi Washio (Program Committee Chair) Division of Intelligent Systems Science, The Institute of Scientific and Industrial Research, Osaka University 8-1 Mihogaoka, Ibaraki, Osaka 567-0047, Japan Phone: +81-6-6879-8541 Fax: +81-6-6879-8544 E-mail: [EMAIL PROTECTED] ---------------------------------------------------- Takashi Washio Institute for the Scientific and Industrial Research (I.S.I.R), Osaka University 8-1, Mihogaoka, Ibarakishi, Osaka 567-0047, Japan Phone : +81-6-6879-8541 Fax : +81-6-6879-8544 E-mail: [EMAIL PROTECTED] ------------------- MLnet community list http://www.mlnet.org/mlnet2/services/mlnet-community.html
