Invited Session on "Data Science for Big Data" in KES 2019 (
4-6 September, 2019, Budapest, Hungary.

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

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Submissions for the conference must be made as complete papers (there is no abstract submission stage) submitted as PDF documents through PROSE online submission and review system.

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

Guidance notes for the preparation of Full Papers is available .. here ..

An MS Word template is available (7.1Mbyte .zip archive) .. here ..

A LaTeX template is available (5.6Mbyte .zip archive) .. here ..

The paper format as a PDF document is available .. here ..

Please consult important FAQs about document preparation to be found .. here ..


Submission of papers: 10 May 2019
Notification of acceptance: 17 May 2019
Final paper to be received by: 27 May 2019 3 June 2019


Data Science 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:
Katsutoshi Yada, Professor, Kansai University
Takahira Yamaguchi, Professor, Keio University

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

[Contact email for this session]

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