This invited session focuses on service science for innovation and data mining, one of its key technologies. In service science, data mining which discovers useful knowledge from large scale data is an important technology which provides a scientific basis as a spark for innovation. In this session, we aim to attract researchers in data mining (computer science, etc.) and service related fields, and encourage sharing of information among them.

Technical issues include (but not limited to)

<Techniques>
Data mining
Machine learning
Text and semi-structured data mining
Pattern recognition
Knowledge representation
Statistics and probability

<Service Applications>
Engineering
Management
Marketing
Operation process
Medical treatment
Public administration
Service Ontologies and Modeling

All Invited Session papers should be submitted through PROSE online paper submission system. (PROSE submission system will open soon.) Please follow the instructions at the KES 2010 website.
KES 210 submission system (PROSE)
http://www.prosemanager1.co.uk/kes2010is/login.asp
Please select IS18 "Data Mining and Service Science for Innovation"

Papers will be reviewed by independent experts for their originarity, significance, creativity and applicability. All accepted papers must be presented by one of the authors who must register and pay fees.

The papers should be no longer than 10 pages in LNCS format.

SPONSOR
DSI Project in Kansai University

Data Mining Laboratory in Kansai University
IEEE SMCS, Technical Committee on Information Systems for Design and Marketing