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DMS 2014 : CFP: 2014 IEEE International Workshop on Data Mining for Service (DMS2014)


When Dec 14, 2014 - Dec 14, 2014
Where Shenzhen, China.
Submission Deadline Aug 1, 2014
Notification Due Sep 26, 2014
Categories    data mining   big data   statistics and probability   marketing science

Call For Papers

IEEE International Workshop on Data Mining for Service (DMS2014)
December 14, 2014, Shenzhen, China.

IEEE International Workshop on Data Mining for Service (DMS2014) held in conjunction with The 2014 IEEE International Conference on Data Mining (ICDM'14), Shenzhen, China, December 14, 2014.


In midst of service applications in engineering and the increasing importance of the service sector in the global economy, services are being scientifically and much attention is being focused on service science as a means to improve productivity. Since services are amorphous (they have no sharp) 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.

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
* Data-oriented service innovation
* Case studies of data mining applications for service science
Especially, this year, we focus on the topics related to Big Data in the workshop. This workshop will discuss specific uses of data mining techniques for Big Data to create new service. Possible topics of interest include below:
* New service and Big Data
* Novel model and Big Data
* Any service application of data mining using Big Data

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.

Paper submissions should be limited to a maximum of 10 pages in the IEEE 2-column format. More detailed informations are available in the IEEE ICDM 2014 Submission Guidelines.

Please submit your manuscript through the IEEE ICDM Workshop CyberChair submission system. Papers will be reviewed by at least two independent experts for their originality, significance, creativity and applicability.

All papers accepted for the workshop will be included in the ICDM'14 Workshop Proceedings published by the IEEE Computer Society Press. Therefore papers that have already been accepted or are currently under review for other conferences or journals will not be considered for ICDM and DMS'14. All accepted papers must be presented by one of the authors who must register and pay fees.

Submissions due: August 1, 2014
Notifications of Acceptance: September 26, 2014
Workshop day: December 14, 2014

Workshop Co-chairs
Shusaku Tsumoto, Shimane University, Japan
Katsutoshi Yada, Kansai University, Japan (Contact Person)
PC member
Daniel Baier, Brandenburg University of Technology Cottbus, Germany.
Kuiyu Chang, Nanyang Technological University, Singapore.
Michelle Chen, San Jose State University, USA.
Yan Chow, Kaiser Permanente Information Technology, USA
Jiming Liu, Hong Kong Baptist University, Hong Kong.
Peter DE Maeyer, Singapore Management University, Singapore.
Reinhold Decker, Bielefeld University, Germany.
Naoki Katoh, Kyoto University, Japan.
Rajeev Kohli, Columbia University, USA.
Oded Koenigsberg, Columbia University, USA.
Hiroshi Nakajima, OMRON, Japan
Oded Netzer, Columbia University, USA.
Dirk Van den Poel, Ghent University, Belgium.
Roman Slowinski, Poznan Institute of Technology, Poland
Takashi Washio, Osaka University, Japan.

Katsutoshi Yada
Faculty of Commerce, Kansai University
3-3-35, Yamate, Suita, Osaka, 564-8680, Japan

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