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Peer-to-peer usage analysis in dynamic databases

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Abstract

With the rapid growth of Internet and computer techniques, the huge number of information is thus available to be analyzed for modeling user behaviors. Peer-to-peer architecture provides the large-scale community behaviors for information exchanging and sharing. Usage behaviors can be defined as the sequential order as the requests or downloads performed on each node in P2P system. Sequential pattern mining (SPM) can be used to discover usage behaviors to facilitate efficient decision-making. In the past, the fast updated sequential pattern (FUSP)-tree structure was proposed for handling sequence insertion and sequence deletion without candidate generation. Transaction modification is, however, also an important issue in real-world applications. In this paper, a maintenance (FUSP-TREE-MOD) algorithm to efficient update FUSP-trees for sequence modification in dynamic databases is proposed. The proposed approach can thus enhance behaviors modeling in dynamic P2P system for extracting sequential patterns or relationships occurring in a large number of nodes. Experimental results indicate that the proposed algorithm outperforms batch approaches in maintaining discovered sequential patterns.

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Acknowledgment

This research was partially supported by the Shenzhen Peacock Project, China, under grant KQC201109020055A, by the Natural Scientific Research Innovation Foundation in Harbin Institute of Technology under grant HIT.NSRIF.2014100, and by the Shenzhen Strategic Emerging Industries Program under grant ZDSY20120613125016389.

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Authors and Affiliations

  1. School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, HIT Campus Shenzehn University Town, Xili, Shenzhen, 518055, People’s Republic of China

    Chun-Wei Lin

  2. Innovative Information Industry Research Center (IIIRC), School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen City, Guangdong Province, China

    Wensheng Gan

  3. Innovative Information Industry Research Center (IIIRC), Shenzhen Key Laboratory of Internet Information Collaboration, Harbin Institute of Technology Shenzhen Graduate School, HIT Campus Shenzehn University Town, Xili, Shenzhen, 518055, People’s Republic of China

    Chun-Wei Lin

  4. Department of Computer Science and Information Engineering, National University of Kaohsiung, Kaohsiung, Taiwan, Republic of China

    Tzung-Pei Hong

  5. Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan, Republic of China

    Tzung-Pei Hong

  6. Global Science Experimental Data Hub Center, Korea Institute of Science and Technology Information, Seoul, South Korea

    Sang Oh Park

  7. Department of Electrical Engineering, National Cheng Kung University, Tainan City, Taiwan

    Bo-Wei Chen

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  1. Chun-Wei Lin
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Correspondence to Chun-Wei Lin.

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Lin, CW., Gan, W., Hong, TP. et al. Peer-to-peer usage analysis in dynamic databases. Peer-to-Peer Netw. Appl. 8, 851–862 (2015). https://doi.org/10.1007/s12083-014-0290-2

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  • DOI: https://doi.org/10.1007/s12083-014-0290-2

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