人工知能学会論文誌
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PageRank のための高速なTop-k 検索
藤原 靖宏中辻 真塩川 浩昭三島 健鬼塚 真
著者情報
キーワード: graph mining, efficient, top-k seach
ジャーナル フリー

30 巻 (2015) 2 号 p. 473-478

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In AI communities, many applications utilize PageRank. To obtain high PageRank score nodes, the original approach iteratively computes the PageRank score of each node until convergence from the whole graph. If the graph is large, this approach is infeasible due to its high computational cost. The goal of this study is to find top-k PageRank score nodes efficiently for a given graph without sacrificing accuracy. Our solution, F-Rank, is based on two ideas: (1) It iteratively estimates lower/upper bounds of PageRank scores, and (2) It constructs subgraphs in each iteration by pruning unnecessary nodes and edges to identify top-k nodes. Experiments show that F-Rank finds top-k nodes much faster than the original approach.

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© 人工知能学会 2015
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