Active caching for similarity queries based on shared-neighbor information

Michael E. Houle, Vincent Oria, Umar Qasim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

Novel applications such as recommender systems, uncertain databases, and multimedia databases are designed to process similarity queries that produce ranked lists of objects as their results. Similarity queries typically result in disk access latency and incur a substantial computational cost. In this paper, we propose an 'active caching' technique for similarity queries that is capable of synthesizing query results from cached information even when the required result list is not explicitly stored in the cache. Our solution, the Cache Estimated Significance (CES) model, is based on shared-neighbor similarity measures, which assess the strength of the relationship between two objects as a function of the number of other objects in the common intersection of their neighborhoods. The proposed method is general in that it does not require that the features be drawn from a metric space, nor does it require that the partial orders induced by the similarity measure be monotonic. Experimental results on real data sets show a substantial cache hit rate when compared with traditional caching approaches.

Original languageEnglish (US)
Title of host publicationCIKM'10 - Proceedings of the 19th International Conference on Information and Knowledge Management and Co-located Workshops
Pages669-678
Number of pages10
DOIs
StatePublished - 2010
Event19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10 - Toronto, ON, Canada
Duration: Oct 26 2010Oct 30 2010

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Other

Other19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10
CountryCanada
CityToronto, ON
Period10/26/1010/30/10

All Science Journal Classification (ASJC) codes

  • Decision Sciences(all)
  • Business, Management and Accounting(all)

Keywords

  • Performance

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