International Journal of Information Technology and Computer Science (IJITCS)
IJITCS Vol. 6, No. 12, 8 Nov. 2014
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MAROR: Multi-Level Abstraction of Association Rule Using Ontology and Rule Schema
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Author(s)
Index Terms
Multi-Level Rule Synthesis, Local Pattern Analysis, Global Rules, Exceptional Rules, Rule Schema
Abstract
Many large organizations have multiple databases distributed over different branches. Number of such organizations is increasing over time. Thus, it is necessary to study data mining on multiple databases. Most multi-databases mining (MDBM) algorithms for association rules typically represent input patterns at a single level of abstraction. However, in many applications of association rules – e.g., Industrial discovery, users often need to explore a data set at multiple levels of abstraction, and from different points of view. Each point of view corresponds to set of beliefs (and representational) commitments regarding the domain of interest. Using domain ontologies, we strengthen the integration of user knowledge in the mining and post-processing task. Furthermore, an interactive and iterative framework is designed to assist the user along the analyzing task at different levels. This paper formalizes the problem of association rules using ontologies in multi-database mining, describes an ontology-driven association rules algorithm to discoverer rules at multiple levels of abstraction and presents preliminary results in petroleum field to demonstrate the feasibility and applicability of this proposed approach.
Cite This Paper
Salim Khiat, Hafida Belbachir, Sid Ahmed Rahal, "MAROR: Multi-Level Abstraction of Association Rule Using Ontology and Rule Schema", International Journal of Information Technology and Computer Science(IJITCS), vol.6, no.12, pp.24-34, 2014. DOI:10.5815/ijitcs.2014.12.04
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