Semantic Business Analysis ModelConsidering Association Rules Mining

Anna Rozeva, Boryana Deliyska, Roumiana Tsankova


Deriving models for intelligent business analysis by generation of knowledge through data mining techniques has proved to be highly theoretically researched and practically implemented topic in the field of decision support and business intelligence systems in the last decade. A general data mining task concerns discovery and description of relationships among items recorded in business transactions. The model of association rules is the one most implemented for revealing such relationships. In order to increase the decision support value of the output associative models the necessity for capturing and involving semantics from the domain of discourse has emerged. Ontologies represent the tool for structuring the concepts and their relationships as knowledge for a subject area that was established with the growth of the Semantic Web. The paper is intended to design a framework for implementing ontologies in the association rule analysis model that provides for involving semantics in the extracted rules by means of initial verification and optimization of the mining task by database scheme ontology and exploration of rules’ interestingness by ontology reasoning process.


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Paper Citation

in Harvard Style

Rozeva A., Deliyska B. and Tsankova R. (2012). Semantic Business Analysis ModelConsidering Association Rules Mining . In Proceedings of the Second International Symposium on Business Modeling and Software Design - Volume 1: BMSD, ISBN 978-989-8565-26-6, pages 122-127. DOI: 10.5220/0004461801220127

in Bibtex Style

author={Anna Rozeva and Boryana Deliyska and Roumiana Tsankova},
title={Semantic Business Analysis ModelConsidering Association Rules Mining},
booktitle={Proceedings of the Second International Symposium on Business Modeling and Software Design - Volume 1: BMSD,},

in EndNote Style

JO - Proceedings of the Second International Symposium on Business Modeling and Software Design - Volume 1: BMSD,
TI - Semantic Business Analysis ModelConsidering Association Rules Mining
SN - 978-989-8565-26-6
AU - Rozeva A.
AU - Deliyska B.
AU - Tsankova R.
PY - 2012
SP - 122
EP - 127
DO - 10.5220/0004461801220127