MRAR: Mining Multi-Relation Association Rules
محل انتشار: مجله محاسبات و امنیت، دوره: 1، شماره: 2
سال انتشار: 1393
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 169
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شناسه ملی سند علمی:
JR_JCSE-1-2_006
تاریخ نمایه سازی: 8 دی 1400
چکیده مقاله:
In this paper, we introduce a new class of association rules (ARs) named"Multi-Relation Association Rules" which in contrast to primitive ARs (thatare usually extracted from multi-relational databases), each rule item consistsof one entity and several relations. These relations indicate indirect relationshipbetween entities. Consider the following Multi-Relation Association Rule wherethe first item consists of three relations live in, nearby and humid: "Those wholive in a place which is near by a city with humid climate type and also areyounger than ۲۰ → their health condition is good". A new algorithm calledMRAR is proposed to extract such rules from directed graphs with labelededges which are constructed from RDBMSs or semantic web data. Also, thequestion "how to convert RDBMS data or semantic web data to a directed graphwith labeled edges?" is answered. In order to evaluate the proposed algorithm,some experiments are performed on a sample dataset and also a real-world drugsemantic web dataset. Obtained results confirm the ability of the proposedalgorithm in mining Multi-Relation Association Rules.
کلیدواژه ها:
نویسندگان
Reza Ramezani
Department of Computer Engineering, Ferdowsi University of Mashhad
Mohamad Saraee
Electrical & Computer Engineering, Isfahan University of Technology, Iran.
Mohammad Ali Nematbakhsh
Department of Computer Engineering, University of Isfahan, Iran