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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Electrical Engineering and Computer Science
Wei Dai
Hubei Polytechnic University
Computer Science & IT

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Research on Community Detection Algorithm Based on the UIR-Q Zilong Jiang; Wei Dai; Liangchen Chen; Xiufeng Cao; Yanling Shao
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 2: June 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i2.2685

Abstract

Aiming at the current problems of community detection algorithm in which user’s property is not used; the community structure is not stable and the efficiency of the algorithm is low, this paper proposes a community detection algorithm based on the user influence and its parallelization method. In terms of the concept of user influence in the subject communication and the PageRank algorithm, this paper uses the properties of nodes of users in social networks to form the user influence factors. Then, the user with the biggest influence is set as the initial node of new community and and the local modularity is introduced into detecting the community structure.  in order to make the result of community detection quick and efficient. Many experiments show that the improved algorithm can efficiently detect the community structure with large scale users and the results are stable. Therefore, this algorithm will have a wide applied prospect.
Research on Personalized Behaviors Recommendation System Based on Cloud Computing Wei Dai; Peng Hu
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: February 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Data scale becomes a bottleneck in user behaviors analysis, many data mining algorithms become Inefficient slow in this circumstances. This paper explores an effective approach to mine latent knowledge in large scale data, which combines the basal principles of association rules, MapReduce model and Hbase database. First, general principles and algorithm of association rules are given. Second, the work mechanism and traits of MapReduce model and HBase are introduced. Finally, it gives detailed design methods that how to combine the basal principles of association rules, MapReduce model and Hbase database. Sufficient experiments prove that the processing velocity of parallel approach nearly decuple unparallel approach’s. Therefore, the approach combined association-rule and cloud computing is a successful and valuable exploration. DOI : http://dx.doi.org/10.11591/telkomnika.v12i2.3443
Co-Authors Liangchen Chen Peng Hu Xiufeng Cao Yanling Shao Zilong Jiang