Data Mining and Serice Science for Innovation 本文へジャンプ
Invited Session on "Data Mining and Service Science for Innovation"
in KES 2013

Invited Session on "Data Mining and Service Science for Innovation"
http://www2.ipcku.kansai-u.ac.jp/~yada/conf/kes13/
in the KES 2013 (http://kes2013.kesinternational.org/ ).
9-12 September, 2013, in Kitakyushu, Japan.


SCOPE

This special 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.

 



TOPICS

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 Ontologies and Modeling

<Service Applications>

Engineering
Management
Marketing
Operation process
Medical treatment
Public administration


SUBMISSION

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 2013 website.

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.



IMPORTANT DATE
Submission of papers: 12 April, 2013
Notification of Acceptance: 3 May, 2013

Receipt of publication files: 24 May, 2013
Early / Authors Registration Deadline: 1 June, 2013
This is a hard deadline and will not be extended.

Please register as soon as your paper is accepted.


Conference Date: September 9-12, 2013.


SPONSOR
DSI Project in Kansai University

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


CONTACT US
Session Chair:
Katsutoshi Yada (Kansai University, Japan)

Session Co-chair
Takahira Yamaguchi (Keio University, Japan)

Keiji Takai (Kansai University, Japan)



[Contact Person]
Katsutoshi Yada
Director of Data Mining Laboratory, Kansai University.
OSAKA, 564-8680, JAPAN.
http://www2.ipcku.kansai-u.ac.jp/~yada/english/profile.html
E-mail: yadalab.conf@gmail.com