Data Science for Big Data 本文へジャンプ

Invited Session on "Data Science for Big Data"
( ).

15-17 September, 2014, in Gdynia, Poland.

Details of Session (including aim and scope):

This special session focuses on Data Science and Big Data which are two of the hottest research areas in computer science and business. In recent years, Big Data has attracted many researchers and business people in various fields. Big Data is a resource which creates added value by using a data science approach leading to significant innovations. We want to attract researchers and business people whose expertise is related to Big Data and Data Science, and encourage the sharing of information.


Technical issues include (but are not limited to):
Cloud/Grid computing
High performance computing
Data mining
Machine learning
Text and semi-structured data mining
Pattern recognition
Knowledge representation
Statistics and probability
Service Ontologies and Modelling

Operation process
Medical treatment
Public administration


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 2014 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 eight pages in LNCS format.
Full papers should be detailed academic articles in conventional format.
The guide length for full papers is 8 to 10 pages (maximum). .. here ..

* We announce that the paper format has been changed as follows:
Guidance notes for the preparation of Full Papers is available .. here ..
An MS Word template is available .. here ..
A LaTeX template is available .. here ..

Submission of papers: 15 March 2014 11 April 2014
Notification of acceptance: 1 May 2014
Final paper to be received by: 1 June 2014

DSI Project in Kansai University

Data Mining Laboratory in Kansai University

Program Committee
Michelle Chen, University of Connecticut
Michele Gorgoglione, Politecnico di Bari
Naoki Katoh, Kyoto University
Wataru Sunayama, Hiroshima City University
Shusaku Tsumoto, Shimane University
Dirk Van den Poel, Ghent University
Takashi Washio, Osaka University

Session Chair:
Yada, Katsutoshi (Kansai University, Japan)
Takahira Yamaguchi, Keio University

[Contact Person]
Katsutoshi Yada, Ph.D.
Professor of Management Information System
Data Mining Laboratory, Kansai University.
OSAKA, 564-8680, JAPAN.

[Contact email for this session]