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A Top-r k Influential Community Search Algorithm

Volume 14, Number 11, November 2018, pp. 2553-2560
DOI: 10.23940/ijpe.18.11.p11.26522662

Wei Chena,b, Jia Liua,b, Ziyang Chena,c, and Jianqi Chena

aSchool of Information Science and Engineering, Yanshan University, Qinhuangdao, 066004, China
bDepartment of Information Engineering, Hebei University of Environmental Engineering, Qinhuangdao, 066102, China
cSchool of Information and Management, Shanghai Lixin University of Accounting and Finance, Shanghai, 201620, China

(Submitted on August 6, 2018; Revised on September 10, 2018; Accepted on October 26, 2018)

Abstract:

Top-r k influential community search is one of the hot topics in social network research, the solution of which usually adapts the “index + query” strategy. Aiming at the problems of low index efficiency and unreasonable metric of the influence, we first propose a new index construction method that not only improves the efficiency of constructing index but also reduces the index size. In the community search, the metric of the influence on the community is redefined and the search algorithm is proposed on this basis to make the search results more practical. Finally, according to experiments on 12 datasets, we verify the high efficiency of the method proposed in this paper compared with the existing methods from the following aspects including the index construction time, the index size, and the search time.

 

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