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Authors: Jan Kupčík 1 and Tomáš Hruška 2

Affiliations: 1 Brno University of Technology, Czech Republic ; 2 Brno University of Technology and IT4Innovations Centre of Excellence, Czech Republic

ISBN: 978-989-8565-13-6

Keyword(s): Data Mining System, Knowledge Discovery, Data Stream, OLAP.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Knowledge Engineering ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Software Engineering ; Symbolic Systems

Abstract: As the amount of generated and stored data in enterprises increases, the significance of fast analyzing of this data rises. This paper introduces data mining system designed for high performance analyses of very large data sets, and presents its principles. The system supports processing of data stored in relational databases and data warehouses as well as processing of data streams, and discovering knowledge from these sources with data mining algorithms. To update the set of installed algorithms the system does not need a restart, so high availability can be achieved. Data analytic tasks are defined in a programming language of the Microsoft .NET platform with libraries provided by the system. Thus, experienced users are not limited by graphical designers and their features and are able to create complex intelligent analytic tasks. For storing and querying results a special storage system is outlined.

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Paper citation in several formats:
Kupčík, J. and Hruška, T. (2012). Towards Online Data Mining System for Enterprises.In Proceedings of the 7th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE, ISBN 978-989-8565-13-6, pages 187-192. DOI: 10.5220/0004098101870192

@conference{enase12,
author={Jan Kupčík. and Tomáš Hruška.},
title={Towards Online Data Mining System for Enterprises},
booktitle={Proceedings of the 7th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,},
year={2012},
pages={187-192},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004098101870192},
isbn={978-989-8565-13-6},
}

TY - CONF

JO - Proceedings of the 7th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,
TI - Towards Online Data Mining System for Enterprises
SN - 978-989-8565-13-6
AU - Kupčík, J.
AU - Hruška, T.
PY - 2012
SP - 187
EP - 192
DO - 10.5220/0004098101870192

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