WORKSHOP
The Fourth Workshop on Data Mining for Service (DMS2013) held in
conjunction with
The 2013 IEEE International Conference on Data Mining (ICDM'2013),
Dallas, Texas,
December 8th, 2013. December 7th, 2013.
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
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.
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
SUBMISSION & PUBLICATION
Paper submissions should be limited to a maximum of 10
pages, and follow the IEEE ICDM format. More detailed informations are available in
the IEEE ICDM 2013 Submission Instructions.
Please submit your manuscript through the DMS 2013 submission site.
All accepted papers will be included in the ICDM'13 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.
IMPORTANT DATE
Submissions due:August 3rd, 2013. August 17th, 2013.
Notifications of Acceptance: September 24, 2013
Workshop day: December 8th, 2013. December 7th, 2013.
WORKSHOP ORGANIZATION
Workshop-Chair
- Shusaku Tsumoto, Shimane University, Japan
- Katsutoshi Yada, Kansai University, Japan
Program Committee
- 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
- Peter DE Maeyer, Singapore Management University, Singapore
- Reinhold Decker, Bielefeld University, Germany
- Naoki Katoh, Kyoto University, Japan
- Rajeev Kohli, Columbia University, USA
- Oded Koenigsberg, London Business School, England
- 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
LINKs
Sponsors
- Data Mining Laboratory in Kansai University
(Funded by Strategic Project to Support the Formation of Research Bases at Private Universities) - IEEE SMCS, Technical Committee on Information Systems for Design and Marketing
Past Workshops
CONTACT US
Katsutoshi YADA
Faculty of Commerce, Kansai University
3-3-35, Yamate-cho, Suita-shi,
OSAKA, 564-8680, JAPAN
E-mail: ieee.dms
gmail.com
Tel: +81-6-6368-1121(ex.5392)
