loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

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

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.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.222.182.105

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

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 - ENASE; ISBN 978-989-8565-13-6; ISSN 2184-4895, SciTePress, 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 - ENASE},
year={2012},
pages={187-192},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004098101870192},
isbn={978-989-8565-13-6},
issn={2184-4895},
}

TY - CONF

JO - Proceedings of the 7th International Conference on Evaluation of Novel Approaches to Software Engineering - ENASE
TI - Towards Online Data Mining System for Enterprises
SN - 978-989-8565-13-6
IS - 2184-4895
AU - Kupčík, J.
AU - Hruška, T.
PY - 2012
SP - 187
EP - 192
DO - 10.5220/0004098101870192
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic