submit the paper to the session organizer by email directly.
#1. Optimization-based Data Mining Techniques and Applications
Scope/Topic :For last ten years, the researchers have extensively applied quadratic programming into classification, known as V. Vapnik…s Support Vector Machine, as well as various applications. However, using optimization techniques to deal with data separation and data analysis goes back to more than thirty years ago. According to O. L. Mangasarian, his group has formulated linear programming as a large margin classifier in 1960…s. In 1970…s, A. Charnes and W.W. Cooper initiated Data Envelopment Analysis where a fractional programming is used to evaluate decision making units, which is economic representative data in a given training dataset. From 1980…s to 1990…s, F. Glover proposed a number of linear programming models to solve discriminant problems with a small sample size of data. Then, since 1998, the organizers and their colleagues extended such a research idea into classification via multiple criteria linear programming (MCLP) and multiple criteria quadratic programming (MQLP), which differs from statistics, decision tree induction, and neural networks. So far, there are hundreds of scholars around the world have been actively working on the field of using optimization techniques to handle data mining problems. This workshop will call for papers to the researchers in the above interface fields for their participation in the conference. In addition to attract the technical papers, this workshop will particularly encourage the submissions of optimization-based data mining applications, such as customer segmentation, credit assessment management, fraud detection, information intrusion, bio-informatics, etc.
Motivations why a NCM special session on this topic should take place
Many data mining tasks, such as classification, prediction, clustering, and model selection, can be formulated as optimization problems. Optimization techniques have great potentials in data mining and business intelligence. However, most current research of optimization-based data mining focus on model development and algorithm design, other steps in the Knowledge Discovery Process did not get enough attention. This workshop intends to promote the research interests in the connection of optimization and data mining in the whole KDD process, including data cleaning, data preparation, data transformation, model construction, results evaluation and knowledge presentation, as well as real-life applications among the growing data mining communities.
A preliminary list of reviewers:
- S. Aoki, Osaka Prefecture University, Japan
- W. Chaovalitwongse, Rutgers State University of New Jersey, USA
- M. Koda, University of Tsukuba, Japan
- K. K. Lai, City University of Hong Kong, Hong Kong, China
- D. Olson, University of Nebraska at Lincoln, USA
- J. Peng, University of Illinois at Urbana-Champaign, USA
- DA de Waal, North-West University, South Africa
- Edward W. Wild, University of Wisconsin, USA
- J. Wang, Montclair State University, USA
- X. Yang, Daresbury Laboratory, Warrington, UK
- N. Zhong, Maebashi Institute of Technology, Japan
A list of potential authors:
More than three hundred potential authors in this research area will be contacted. The organizers have successfully organized a workshop of related topic in IEEE International Conference on Data Mining for 3 times and every year we received at least 40 submissions.
Co-Chairs
Dr.Yong Shi
College of Information Science and Technology, University of Nebraska at Omaha, NE 68182, USA
Chinese Academy of Sciences Research Center on Fictitious Economy and Data Science
Beijing 100080, China
Dr.Yi Peng
School of Management and Economics, University of Electronic Science and Technology of China, Chengdu 610054, China
Dr.Gang Kou
School of Management and Economics, University of Electronic Science and Technology of China, Chengdu 610054, China
Contact Information
Name : Gang Kou | E-mail : kougang@yahoo.com
Address : 610 Opperman Drive, Eagan, MN 55123, USA
#2. Artificital Intelligence Application on Mobile Commerce and Ubiquitious Services (AIMCUS)
Scope/Topic :1. Case and empirical study about mobile commerce and ubiquitious services.
2. AI techniques for mobile Commerce customer behaviour analysis.
3. AI techniques for ubiquitious services requirement analysis.
4. AI techniques for personalization and recommendation system.
5. AI techniques for ubiquitious web Service.
6. AI techniques for search engine of web service.
7. AI techniques for diffusion of ubiquitious services.
8. AI techniques for mobile commerce transaction analysis
9. Business Model of Mobile commerce used ubiquitious service
10. Not limited above but related.
Contact Information
Name : Chen-Shu Wang | E-mail : 93356506@nccu.edu.tw
Address : Department of MIS, National Cheng-Chi University,64, Sec. 2, Chihnan Rd., Taipei 116, Taipei
#3. Artificial Intelligence in Grid Computing
Scope/Topic :Artificial Intelligence methodology plays a very important role in Advanced Distributed Systems, especially Grid Computing. Some thoughts of intelligence can strengthen and enhance the performance considering the problem of optimizing functions. The integration of these aspects will bring the new inspiration to us.
The main aims of this workshop are to highlight the latest scientific advances within the Artificial Intelligence and Distributed Computing. The objective is to provide a forum for researchers to present new ideas and contributions in the form of technical papers.
Topics:
Grid Computing
Distributed Computing
Intelligence Control Methods in Distributed Computing
Intelligence Methods for Resource Allocation, Task Scheduling, Grid Service Publishing, Finding and Composing
Security Techniques and Methods
Resource Management System Architecture
Fractal Theory
Fuzzy Logic
Neural Networks
Genetic Algorithms
Intelligent Agents
Digital Signal Processing
Chaos Theory
Other topics
Contact Information
Name : Kun Gao | E-mail : gaoyibo@gmail.com
Address : No. 8, South Qian Hu Road, Ningbo, Zhejiang, China 315100
#4. Supply Chain Risk Management
DescriptionRisk management within supply chains is one of the most significant challenges facing every organization. This is because all organizations are members of at least one or more unpredictable supply chains. Therefore, supply chain risk management (SCRM) has become an important emergent research field in recent years. However, there are few researches working on the specific dimensions of SCRM. In this context, SCRM is a new research field especially in petroleum, agro-food, automotive, electronics and other industries. This special session encourages the use of operations research methods and empirical study methodologies to explore the SCRM.
Emphasis will be placed on information and performance measurement in a global supply chain. The prime objective of the special session is to encourage original works that demonstrates the application of operations research/management techniques and other related empirical methodologies in SCRM. .
Submission Topics
- Developing strategic SC decisions considering risk
- Evaluating risks in supply chains
- Assessing the security risk in SCM
- Outsourcing risk management
- Modeling of SC risk models
- Collaborative supply chain and information risk management
- Cost and risk considerations in supply chain management
- Stochastic supply chain and networked computing
- Suppy chain inventory risk management.
Important Dates
Paper Submission Deadline: 7,June 2008
Deadline for special sessions paper to the system: Before June 12.
Deadline for final camera ready paper to IEEE's system: June 20
Organizers
Prof. Hui-Ming Wee
Chung Yuan Christian University/ Curtin University of Technology
weehm@cycu.edu.tw
Prof. Mohammed Quaddus
Graduate School of Business, Curtin University of Technology, Perth, WA 6845, Australia
mohammed.quaddus@gsb.curtin.edu.au
Contact Information
Name : HUI-MING WEE | E-mail : weehm@cycu.edu.tw
Address : 200, Chung Pei Road, Chungli, Taiwan 320