@inproceedings{c73acd2cca684d54b008d477ecf791bd,
title = "A partial-order based active cache for recommender systems",
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.",
keywords = "Caching, Query optimization",
author = "Umar Qasim and Vincent Oria and Wu, {Yi Fang Brook} and Houle, {Michael E.} and {\"O}zsu, {M. Tamer}",
note = "Copyright: Copyright 2010 Elsevier B.V., All rights reserved.; 3rd ACM Conference on Recommender Systems, RecSys'09 ; Conference date: 23-10-2009 Through 25-10-2009",
year = "2009",
doi = "10.1145/1639714.1639750",
language = "English (US)",
isbn = "9781605584355",
series = "RecSys'09 - Proceedings of the 3rd ACM Conference on Recommender Systems",
pages = "209--212",
booktitle = "RecSys'09 - Proceedings of the 3rd ACM Conference on Recommender Systems",
}