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General Information
    • ISSN: 2301-3559
    • Frequency: Quarterly
    • DOI: 10.18178/LNSE
    • Editor-in-Chief: Prof. Jemal Antidze
    • Executive Editor: Ms. Nina Lee
    • Abstracting/ Indexing: EI (INSPEC, IET), DOAJ, Electronic Journals Library, Engineering & Technology Digital Library, Ulrich's Periodicals Directory, International Computer Science Digital Library (ICSDL), ProQuest and Google Scholar.
    • E-mail: lnse@ejournal.net
Editor-in-chief
Prof. Jemal Antidze
I. Vekua Scientific Institute of Applied Mathematics
Tbilisi State University, Georgia
I'm happy to take on the position of editor in chief of LNSE. We encourage authors to submit papers concerning any branch of Software Engineering.

LNSE 2014 Vol.2(3): 275-281 ISSN: 2301-3559
DOI: 10.7763/LNSE.2014.V2.136

A Distributed Rule Engine Based on Message-Passing Model to Deal with Big Data

Jinghan Wang, Rui Zhou, Jing Li, and Guowei Wang
Abstract—Rule engine is a good way of knowledge representation and inference. It has been extensively studied and used in artificial intelligence. However, because of its low computational efficiency and the limitation of single machine’s capacity, it cannot deal well with big data. In order to address this problem, we propose a distributed implementation of the rule engine based on message-passing model. It is designed to make use of multiple machines in a computing cluster to deal with a large amount of data in a parallel and distributed way. This paper not only describes details of the design and implementation of it, but also shows its high performance through several experiments.

Index Terms—Artificial intelligence, big data, distributed rule engine, message-passing model.

Jinghan Wang, Rui Zhou, Jing Li, and Guowei Wang are with the School of Computer Science and Technology, University of Science and Technology of China (USTC), China (e-mail: heiswjh@mail.ustc.edu.cn, rayzhou@mail.ustc.edu.cn, lj@ustc.edu.cn).

[PDF]

Cite: Jinghan Wang, Rui Zhou, Jing Li, and Guowei Wang, "A Distributed Rule Engine Based on Message-Passing Model to Deal with Big Data," Lecture Notes on Software Engineering vol. 2, no. 3, pp. 275-281, 2014.

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