Paper and Program

Important Dates


Paper Submission Due December 29, 2004, 24:00 Pacific Standard Time (PST)
Notification of Acceptance/Rejection February 27, 2005
Camera-ready Copy Due March 10, 2005
Workshop Proposals Due December 22, 2004
Workshop Notifications January 10, 2005
Tutorial Proposals Due February 12, 2005
Tutorial Notifications February 25, 2005
Conference May 18-20, 2005



Call for Papers


The 9th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-05)

Melia Hanoi Hotel, Hanoi, Vietnam
18-20 May 2005

http://www.jaist.ac.jp/PAKDD-05/

(The Call for Papers in PDF format can be downloaded here)

The 9th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-05) is a leading international conference in the areas of data mining and knowledge discovery. It provides an international forum for researchers and industry practitioners to share their new ideas, original research results and practical development experiences from all KDD related areas including data mining, data warehousing, machine learning, databases, statistics, knowledge acquisition and automatic scientific discovery, data visualization, causal induction and knowledge-based systems. The conference calls for research papers reporting original investigation results and industrial track papers reporting real data mining applications and system development experience. The conference also solicits proposals for tutorials on crucial technologies of knowledge discovery and data mining, and calls for workshop proposals focusing on specific new challenges and emergency issues of knowledge discovery and data mining.

Topics

The conference calls for research papers reporting original investigation results and industrial track papers reporting real data mining applications and system development experience.The topics of the PAKDD-05 papers fall into two major categories which will include but are not limited to the following:

Data Mining Foundations Data Mining in Specialized Domain
  • Theoretic Foundations
  • Novel Algorithms
  • Association Rules
  • Classification and Ranking
  • Clustering
  • Text Mining
  • Machine Learning Methods
  • Statistical Methods
  • Privacy Preserving Data Mining
  • Parallel and Distributed Data Mining
  • Interactive and Online Mining
  • KDD Process and Human Interaction
  • Data and Knowledge Visualization
  • Knowledge Management
  • High Dimensional Data
  • Temporal Data
  • Biomedical Domains
  • Dynamic Data Mining
  • Scientific Databases
  • Semi-structured/unstructured Data
  • Spatial Data
  • Multimedia
  • Web Data and the Internet
  • Integrated Media
  • Security and Intrusion Detection
  • Reliability and Robustness Issues
  • Mining Trends, Opportunities or Risks
  • Integration of Data Warehousing, OLAP and Data Mining
  • Graphic Model Discovery
  • Software Warehouse and Software Mining


Proceedings will be published by Springer Verlag as a volume of LNCS/LNAI series.



Due to many requests, the Program Committee has agreed to extend the deadline of papers submission to 29 December 2004 (see Important Dates).

For any further query, please contact the Program Committee Chairs at the following addresses:

Prof. Ho Tu Bao
Japan Advanced Institute of Science and Technology
1-1 Asahidai Tatsunokuchi Ishikawa 923-1292, Japan
Phone & Fax: +81-761-51-1730
e-mail: bao@jaist.ac.jp

Prof. Huan Liu
Arizona State University
Tempe, AZ 85287-8809, U.S.A.
Tel: 480-727-7349
Fax: 480-965-2751
e-mail: hliu@asu.edu

Prof. David Cheung
University of Hong Kong
Pokfulam Road, Hong Kong, China
Tel: (852) 2859-7072
Fax: (852) 2559-8447
e-mail: dcheung@csis.hku.hk

All submitted papers will be reviewed by at least three PC members on the basis of technical quality, relevance to KDD, originality, significance, and clarity. Accepted papers will appear in proceedings published by Springer-Verlag as part of their LNCS/LNAI Lecture Notes in Artificial Intelligence series. Details about the LNCS/LNAI series can be found at http://www.springer.de/comp/lncs/index.html

Tutorial Proposal Submission

The PAKDD-05 organizing committee invites tutorial proposals in the area of Knowledge Discovery and Data Mining in various topics. A proposal should include a description and outline of the proposed contents; names, affiliations, and biographical sketches of the speaker(s). The intended length of the tutorial is either half-day or full day. For more details of the tutorial proposal, please look at the Tutorial web page at the conference main page.

Tutorial proposals should be submitted (preferably by email) directly to Tutorial Co-Chair no later than February 12, 2005 (see Important Dates).

Takashi Washio
The Institute of Scientific and Industrial Research
Osaka University
8-1 Mihogaoka, Ibaraki, Osaka, 567 Japan
Tel: +81-6-6879-8541
Fax: +81-6-6879-8544
Email: washio@ar.sanken.osaka-u.ac.jp

Workshop Proposal Submission

PAKDD’05 seeks proposals for workshops on novel and emerging areas of Knowledge Discovery & Data Mining, both theoretical and applied. Innovative topics are most welcome. Workshops are intended to serve as forums for discussion of ideas and work of emerging interest, and to promote interactions between experts in disparate areas that do not have standard forums for interaction. Examples of such areas include, but are not restricted to, areas such as security and privacy, reliability, stream processing, results and experience from real-world applications, economic and commercial issues in mining, and so on. Workshops specifically targeted at bringing together practitioners and theoretical researchers are also welcome. These workshops are expected to be either half-day or one-day events.

These workshops are expected to be either half-day or one-day events. Workshop proposals must be sent (preferably by email) directly to Workshop Chair no later than 22 December 2004 (see Important Dates).

Kyuseok Shim
School of Electiral Engineering and Computer Science
Seoul National Univerity
Kwanak P.O. Box 34 Seoul 151-742 Korea
Tel: +82-2-880-07269
Fax: +82-2-871-5974
Email: shim@ee.snu.ac.kr

For more details on workshop proposals, please look at the call for workshop proposals at the conference main page.

Instructions to Authors

Format

The PAKDD-05 Proceedings will be published by Springer Verlag as a volume of LNCS/LNAI series. As a result, authors are strongly encouraged to use Springer's manuscript submission guidelines available at http://www.springer.de/comp/lncs/authors.html for the initial submission. The paper submission length is 12 pages, and the final length for regular paper is 10 and for short papers is 6.

Copyright Form

A copyright form can be downloaded at http://www.springeronline.com/sgw/cda/frontpage/0,10735,5-164-2-72376-0,00.html

Authors of accepted papers are required to complete the copyright form in March 2005 and fax it to +81-761-51-1732 or +81-761-51-1149 (attn: Prof. Ho Tu Bao) at the same time when you submit your final copy (camera ready version).

The volume title and editors of the proceeding to be filled in the Copyright Form are as below:

Volume title: Advances in Knowledge Discovery and Data Mining
Editors: Tu Bao Ho, David Cheung, Huan Liu


Paper Submission

All papers are requested to submit electronically in PDF format via the Conference Management Tool that can be accessed at

https://msrcmt.research.microsoft.com/PAKDD2005/CallForPapers.aspx

PLEASE READ CAREFULLY THE URL BELOW BEFORE MAKING A NEW REGISTRATION
https://msrcmt.research.microsoft.com/pakdd2005/temp/strong_password/

The authors need to fill in the submission form, the paper title and a up to 200 words abstract, and attach their full paper. The submitted papers must not be published or under consideration to be published elsewhere. Each paper will be reviewed by at least three members of the Program Committee.

The deadline of abstract and paper submission has changed to December 29, 2004.

Please inform us to pakdd05@jaist.ac.jp and "Conference Management Toolkit" <cmt@microsoft.com> any problems that may occur when submitting your papers.  We apologize for any inconvenience that may occur in the submission system.


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