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发信人: wenyang (wenyang), 信区: SCU_CS
标 题: PAKDD 2007 Industrial Track Papers征稿
发信站: BBS 蓝色星空站 (Tue Jan 9 20:35:57 2007), 站内
稿件关于数据挖掘的工业应用方面，可以是长文，也可以是短文。稿件一经录用，将在
Lecture Notes on Computer Science上发表，被SCI检索。详情参考下文。
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PAKDD 2007 Call for Industrial Track Papers
The 11th Pacific-Asia Conference on Knowledge
Discovery and Data Mining
(PAKDD 2007)
Nanjing, China
22-25 May, 2007
URL: http://lamda.nju.edu.cn/conf/pakdd07/
As usual, PAKDD 2007 will organize separate sessions for industry oriented
papers. The theme for the industrial sessions is Data Mining for Practitioners.
The industrial sessions will feature keynote speeches by leading industrial
data mining experts, invited talks on new technology trends by leading data
mining technology companies, and paper presentations focussed on solutions to
real world problems in different industry sectors, such as government, banking,
telecommunication, retail, insurance, manufacturing and logistics. Participants
will have opportunities to access both the latest technical advances in data
mining and a showcase of actual applications in industry. Industrial papers on
innovative applications of data mining technology to solve real world problems
are solicited. The following topics are of interest (and indicative but not
limited to):
1. New data mining methodologies
2. Data mining application systems
3. Data cleansing and transformation in data mining
4. New application problems and data mining solutions
5. Data mining in government applications
6. Innovative data mining case studies
Paper Submission
All papers will be fully reviewed by an international committee. The industrial
papers should be submitted to the Indutry Track Chair directly by email
(jhuang@eti.hku.hk). The selected industrial papers will be presented in the
industrial sessions of the main conference, BUT won't be included in the
conference procceedings. Instead, after the conference, outstanding industrial
mining technology companies, and paper presentations focussed on solutions to
real world problems in different industry sectors, such as government, banking,
telecommunication, retail, insurance, manufacturing and logistics. Participants
will have opportunities to access both the latest technical advances in data
mining and a showcase of actual applications in industry. Industrial papers on
innovative applications of data mining technology to solve real world problems
are solicited. The following topics are of interest (and indicative but not
limited to):
1. New data mining methodologies
2. Data mining application systems
3. Data cleansing and transformation in data mining
4. New application problems and data mining solutions
5. Data mining in government applications
6. Innovative data mining case studies
Paper Submission
All papers will be fully reviewed by an international committee. The industrial
papers should be submitted to the Indutry Track Chair directly by email
(jhuang@eti.hku.hk). The selected industrial papers will be presented in the
industrial sessions of the main conference, BUT won't be included in the
conference procceedings. Instead, after the conference, outstanding industrial
papers will be
>included in a LNCS/LNAI Post Proceedings of PAKDD Workshops published by
Springer. To have your industrial papers considered in the post conference
proceedings, at least one author of each industrial paper must register to the
main conference and present the paper in the industrial sessions.
Important Dates
Paper submission: Janurary 20, 2007
Notification: Feburary 26, 2007
Industry Track Co-Chairs
Joshua Zhexue Huang The University of Hong Kong
Yunming Ye Harbin Institute of Technology, China
Committee
Graham Williams, ATO, Australia
Ke Wang, Simon Fraser University, Canada
William Song, University of Durham, UK
Xuelong Li, University of London, UK
Yunming Ye, HIT, China
Warren Jin, CSIRO, Australia
Simeon J. Simoff, University of Technology, Sydney,
Australia
Tao Lin, SAP Research, USA
Xiongfei Li, Jilin University, China
Shuicheng Yan, University of Illinois at
Urbana-Champaign, US
Dacheng Tao, University of London, UK
Wen Jun Yin, IBM China
Yuan Yuan, Aston University, UK
Dong Xu, Columbia University, US
Yoon-Joon Lee, KAIST, Korea
For further inquiries please contact
Dr. Joshua Zhexue Huang
E-Business Technology Institute
The University of Hong Kong
Room G02-G05
Technology Innovation & Incubation Building
Pokfulam Road, Hong Kong, China
Tel: (852) 22990505
Fax: (852) 22990500
Email: jhuang@eti.hku.hk
--
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