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DMS 2016 : IEEE International Workshop on Data Mining for Service


When Dec 12, 2016 - Dec 12, 2016
Where Barcelona, Spain
Submission Deadline Aug 12, 2016
Notification Due Sep 13, 2016
Final Version Due Sep 20, 2016
Categories    big data   data mining   services   innovation

Call For Papers

IEEE International Workshop on Data Mining for Service (DMS2016)
12 December 2016, Barcelona, Spain.

IEEE International Workshop on Data Mining for Service (DMS2016) held in conjunction with The 2016 IEEE International Conference on Data Mining (ICDM'16), Barcelona, Spain, 12 December 2016.


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 8 pages, and follow the IEEE ICDM format. More detailed informations are available in the IEEE ICDM 2016 Submission Guidelines.
Please submit your manuscript through the DMS 2016 submission site.
All accepted papers will be included in the ICDM'16 Workshop Proceedings published by the IEEE Computer Society Press. Therefore, papers must not have been accepted for publication elsewhere or be under review for another workshop, conferences or journals.

Submissions due: August 12, 2016
Notifications of Acceptance: September 13, 2016
Camera-ready paper due: September 20, 2016
Workshop day: December 12, 2016

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-cho, Suita-shi, OSAKA, 564-8680, JAPAN.
Email: yada@

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