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SimRank: a measure of structural-context similarity
Abstract
The problem of measuring "similarity" of objects arises in many applications, and many domain-specific measures have been developed, e.g., matching text across documents or computing overlap among item-sets. We propose a complementary approach, applicable in any domain with object-to-object relationships, that measures similarity of the structural context in which objects occur, based on their relationships with other objects. Effectively, we compute a measure that says "two objects are similar if they are related to similar objects:" This general similarity measure, called SimRank, is based on a simple and intuitive graph-theoretic model. For a given domain, SimRank can be combined with other domain-specific similarity measures. We suggest techniques for efficient computation of SimRank scores, and provide experimental results on two application domains showing the computational feasibility and effectiveness of our approach.
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Metadata
- Authors
- Jeh, G., & Widom, J.
- Venue
- Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
- Publisher
- ACM
- Published
- 2002-07-23
- Pages
- 538-543
- OpenAlex
- W2117831564
- Cited by
- 1,925
- References
- 17
- FWCI
- 8.45
- Type
- conference paper
- Language
- en
- Open access
- closed
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