The Third International Workshop on Data-Mining and Statistical ScienceSpecial Issue @ New Generation Computing Journal
Special Issue on Data-Mining and Statistical Science
We will have a special issue in New Generation Computing. Original papers related to Data-Mining and Statistical Science will be considered for publication.
- Paper Submission Deadline : EXTENDED until January 31, 2009 (closed)
- Paper Submission Format : For the paper style, refer the following two Web pages.
New Generation Computing: Instructions To Authors
The style file for New Generation Computing, ohm-ngc.sty
Important Notes for Submission
- The papers should be submitted to the following E-mail address in PDF format.
- The number of pages should be up to 30
- All fonts must be embedded and the file size must not exceed 2MB.
- In your submission mail, please include the following information in English:
- Title of your paper
- List of all authors and their affiliations
- Name, telephone & facsimile number, office address, and E-mail address of the corresponding author
- E-mail subject should be "NGC special issue: The First Author Name"
- Confirmation E-mail on the paper receipt will be sent for the first author within a few days.
- If you do not have this confirmation E-mail, please contact to the Guest Editor.
E-mail: ngc2008 [AT] sigdmsm.org
Scope of This Issue
The workshop aims at new technology on data mining by combining machine learning techniques in AI and statistical science. In this special issue, we solicit papers on various aspects of data mining from various fields such as AI, statistical science and application domains in order to promote research activities in the fields. The papers for submission should be unpublished elsewhere.
We welcome any papers NOT limited to the presentations appeared in the DMSS2008 workshop.
Target Topics of This Issue
- We solicit papers in the following areas but not limited to:
- Machine Learning
- Probabilistic Reasoning
- Statistical Reasoning
- Data Mining
- Semi-structured Data Mining
- Text Mining
- Data Visualization
- Data Mining Algorithms
- Scalability and Efficiency in Data Mining
- Researches on Data Mining and Statistical Sciences
Editorial Members
Guest Editor
- Takashi Washio
- The Institute of Scientific and Industrial Research (I.S.I.R), Osaka University
Board Members
- Hiroki Arimura
- Graduate School of Information Science and Technology, Hokkaido University
- Ho Tu Bao
- School of Knowledge Science, JAIST
- Tomoyuki Higuchi
- Department of Statistical Modeling, The Institute of Statistical Mathematics
- Toshihiro Kamishima
- Neuroscience Research Institute, National Institute of Advanced Industrial Science and Technology (AIST)
- Yoshinori Kawasaki
- Department of Statistical Modeling, The Institute of Statistical Mathematics
- Hidetoshi Shimodaira
- Graduate School of Information Science and Engineering, Tokyo Institute of Technology
- Masashi Sugiyama
- Graduate School of Information Science and Engineering, Tokyo Institute of Technology
- Kai Ming Ting
- Gippsland School of Information Technology, Monash University, Australia
- Jean-Philippe Vert
- Director of Centre for Computational Biology, ParisTech - Ecole des Mines de Paris, France
- Liwei Wang
- School of Electronic Engineering and Computer Science, Peking University, China