ICDM2002 WORKSHOP
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://kis.maebashi-it.ac.jp/icdm02/workshop.html

Program NEW Click!

Invited Speakers
Professor Saso Dzeroski (Jozef Stefan Institute, Slovenia),
Professor Luc de Raedt (University of Freiburg, Germany),
Professor Stefan Wrobel (Fraunhofer AIS & Univ. Bonn, Germany),


Important Information
Workshop Date : December 9, 2002
Deadline of Paper Submission : September, 30, 2002
Notification of Review Result: October, 15, 2002
Deadline of Camera Ready Copy; November, 4, 2002
Workshop registration fee: $80 for IEEE member, $100 otherwise


Submission
Electronic submissions only. Send a PDF file for
papersubmit@ar.sanken.osaka-u.ac.jp
within 6 pages in IEEE-Computer Society Format.
For MS-Word, PDF and PS files for Style Format:
http://www.computer.org/cspress/instruct.htm
For LaTex files for Style Format:
ftp://pubftp.computer.org/Press/Outgoing/proceedings/IEEE_CS_LaTeX.zip


Important Link
ICDM 2002 (Main URL: http://kis.maebashi-it.ac.jp/icdm02/)

CFP of AM-2002: Call For Participation 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

Workshop Date : December, 9, 2002


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 (CRIEPI, 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: washio@sanken.osaka-u.ac.jp