Proposal and Evaluation of Extraction Method of Community Transition Rules from Social Bookmark Data as Graph Sequence

DOI
  • Yamaguchi Takehiro
    Graduate School of Systems Information Science, Future University Hakodate
  • Niimi Ayahiko
    Faculty of Systems Information Science, Future University Hakodate

Bibliographic Information

Other Title
  • グラフ系列としてのソーシャルブックマークデータからのコミュニティ変化ルールの抽出手法の提案と評価

Abstract

In this study, the data stream transaction data collection, regarded as a graph representing the change in structure and sequence data for each relevant time period, analyzing changes in the sequence graph of the community. The algorithm proposed in this paper, the hierarchical clustering method combined with graph kernel extension, the entire community to analyze the relationship between chart series, occasionally appearing (disappearing in the middle of the series), change the rules of the community extract as. The results of experiments using real Social Bookmark data was shown that changes in the community caught the occasional occurrence of the proposed algorithm.

Journal

Keywords

Details 詳細情報について

  • CRID
    1390282680650070016
  • NII Article ID
    130004591697
  • DOI
    10.14864/fss.27.0.109.0
  • Text Lang
    ja
  • Data Source
    • JaLC
    • CiNii Articles
  • Abstract License Flag
    Disallowed

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