A partial-order based active cache for recommender systems

Umar Qasim, Vincent Oria, Yi Fang Brook Wu, Michael E. Houle, M. Tamer Özsu

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

2 Scopus citations

Abstract

Recommender systems aim to substantially reduce information overload by suggesting lists of similar items that users may find interesting.Caching has been a useful technique for reducing stress on limited resources and improving response time. In this paper, we propose an 'active caching' technique for recommender systems based on a partial order approach that not only benefits from popularity and temporal locality, but also exploits spatial locality. This approach allows the processing of answers to neighboring non-cached queries in addition to the reporting of cached query results. Test results for several data sets and recommendation techniques show substantial improvement in the cache hit ratio and computational costs, while achieving reasonable recall rates.

Original languageEnglish (US)
Title of host publicationRecSys'09 - Proceedings of the 3rd ACM Conference on Recommender Systems
Pages209-212
Number of pages4
DOIs
StatePublished - 2009
Event3rd ACM Conference on Recommender Systems, RecSys'09 - New York, NY, United States
Duration: Oct 23 2009Oct 25 2009

Publication series

NameRecSys'09 - Proceedings of the 3rd ACM Conference on Recommender Systems

Other

Other3rd ACM Conference on Recommender Systems, RecSys'09
CountryUnited States
CityNew York, NY
Period10/23/0910/25/09

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Software

Keywords

  • Caching
  • Query optimization

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