| Autors: Rozeva, A. G., Delijska, B.P., Tsankova, R.S. Title: Semantic business analysis model – considering association rules mining Keywords: Business analysis, knowledge discovery in databases, associa Abstract: 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 th References Issue
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Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus
