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Erschienen in:
2015 | OriginalPaper | Buchkapitel
SimRank Based Top-k Query Aggregation for Multi-Relational Networks
verfasst von : Jing Xu, Cuiping Li, Hong Chen, Hui Sun
Erschienen in: Web-Age Information Management
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SimRank is one measure that compute the similarities between nodes in applications, where the returning of top-k query lists is often required. In this paper, we adopt SimRank as the similarity computation measure and re-write the original inefficient iterative equation into a non-iterative one, we call it Eigen-SimRank. We focus on multi-relational networks, where there may exist different kinds of relationships among nodes and query results may change with different perspectives. In order to compute a top-k query list under any perspective especially compound perspective, we suggest dynamic updating algorithm and rank aggregation methods. We evaluate our algorithms in the experiment section.