Research on Personalized Behaviors Recommendation System Based on Cloud Computing

Wei Dai, Peng Hu

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


Keywords


Cloud computing; Data mining; Association rules; MapReduce; Hbase;

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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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