[AISWorld] CFP: 2010 IEEE International Workshop on Data Mining for Service (DMS 2010, at ICDM 2010)

[Michelle Chen]

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Call for Papers: 2010 IEEE International Workshop on Data Mining for Service (DMS '10)

In conjunction with the 10th IEEE International Conference on Data Mining (ICDM '10)

December 14, 2010, Sydney, Australia

Workshop website: http://www2.ipcku.kansai-u.ac.jp/~yada/conf/dms10/
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Important Dates

Submissions due: July 23, 2010
Notifications of acceptance: September 20, 2010
Camera-ready paper due: October 11, 2010
Workshop day: December 14, 2010

Scope

In midst of service applications in engineering and the increasing importance of the service sector in the global economy, services are being scientific and much attention is being focused on service science as a means to improve productivity. Since services are amorphous (they have no shape) and have the special characteristic of simultaneously causing both production and consumption, it has been difficult to research services in a scientific way. However recently, due to the spread of the internet and technical innovations in sensor networks, huge amounts of data related to all kinds of service activities and processes are being collected, and a new frontier of service research is starting to appear. Given this background, data mining, which can uncover useful knowledge from such masses of data, is expected to take an important role in the development of service science. The focus of this workshop is on empirical findings, methodological papers, and theoretical and conceptual insights related to data mining in the field of various service application areas.

Topics of Interest

The workshop is aimed at bringing together researchers from the areas of the service sector and data mining. We expect to encourage an exchange of ideas and perceptions through the workshop, focused on service and data mining. Possible topics of interest include, but are not limited to:



- Information systems for service to understand consumer behavior

- Information systems to integrate various services

- New data mining applications and new insights for service science

- Case studies of data mining applications for service science



We are interested in the emergence of new business systems in the real business world, and encouraging new applications of data mining in service science. Therefore, submitted papers will be evaluated from the perspectives of traditional criteria such as technical originality and prediction accuracy, while also going beyond to consider creativity and applicability. Case studies that include successes and failures in service science are also welcome.



Technical issues include (but not limited to):



Data Mining

- machine learning algorithms and methods

- text and semi-structured data mining

- pattern recognition

- knowledge representation

- statistics and probability

Areas of Interest
- marketing
- corporate strategy
- finance
- medicine
- nursing care

Examples in Marketing
- marketing science
- consumer behavior
- retailing and pricing
- advertising
- customer relationship management
- brand management
- innovation

Workshop Organizers



Katsutoshi Yada, Kansai University, Japan (Contact Person)
Yukio Ohsawa, University of Tokyo, Japan
Russ Winer, New York University, USA





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H. Michelle Chen
Assistant Professor of Operations & Information Management
School of Business, University of Connecticut
2100 Hillside Rd U1041, Storrs, CT 06269, USA
Email: michelle.chen at business.uconn.edu<mailto:michelle.chen at business.uconn.edu>
Office: +1 (860) 486-6115
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