Salim Khiat

Work place: University of Sciences and Technology-Mohamed Boudiaf (USTOMB)/ Computer Sciences and Mathematics Faculty/ Computer Sciences Department Oran, 31000, Algeria



Research Interests: Software Engineering, Computer Architecture and Organization, Data Mining, Data Structures and Algorithms


Salim Khiat holds a post graduation degree in computer science from University of sciences and technology–Mohamed Boudiaf Oran USTOMB Algeria in 2007. He teaches courses in undergraduate and graduate composition, at National School Polytechnic Oran Algeria. He is memberships in Signal, System and Data Laboratory (LSSD).

His current research interests include the databases, multi-database mining for software engineering, Ontology, grid and cloud computing.

Author Articles
MAROR: Multi-Level Abstraction of Association Rule Using Ontology and Rule Schema

By Salim Khiat Hafida Belbachir Sid Ahmed Rahal

DOI:, Pub. Date: 8 Nov. 2014

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.

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