Browsing by Subject "Query evaluation"
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Item Open Access Adaptive time-to-live strategies for query result caching in web search engines(2012) Alıcı, Sadiye; Altıngövde, I. Ş.; Rıfat, Özcan; Cambazoğlu, B. Barla; Ulusoy, ÖzgürAn important research problem that has recently started to receive attention is the freshness issue in search engine result caches. In the current techniques in literature, the cached search result pages are associated with a fixed time-to-live (TTL) value in order to bound the staleness of search results presented to the users, potentially as part of a more complex cache refresh or invalidation mechanism. In this paper, we propose techniques where the TTL values are set in an adaptive manner, on a per-query basis. Our results show that the proposed techniques reduce the fraction of stale results served by the cache and also decrease the fraction of redundant query evaluations on the search engine backend compared to a strategy using a fixed TTL value for all queries. © 2012 Springer-Verlag Berlin Heidelberg.Item Open Access Incremental cluster-based retrieval using compressed cluster-skipping inverted files(Association for Computing Machinery, 2008-06) Altingovde, I. S.; Demir, E.; Can, F.; Ulusoy, ÖzgürWe propose a unique cluster-based retrieval (CBR) strategy using a new cluster-skipping inverted file for improving query processing efficiency. The new inverted file incorporates cluster membership and centroid information along with the usual document information into a single structure. In our incremental-CBR strategy, during query evaluation, both best(-matching) clusters and the best(-matching) documents of such clusters are computed together with a single posting-list access per query term. As we switch from term to term, the best clusters are recomputed and can dynamically change. During query-document matching, only relevant portions of the posting lists corresponding to the best clusters are considered and the rest are skipped. The proposed approach is essentially tailored for environments where inverted files are compressed, and provides substantial efficiency improvement while yielding comparable, or sometimes better, effectiveness figures. Our experiments with various collections show that the incremental-CBR strategy using a compressed cluster-skipping inverted file significantly improves CPU time efficiency, regardless of query length. The new compressed inverted file imposes an acceptable storage overhead in comparison to a typical inverted file. We also show that our approach scales well with the collection size. © 2008 ACM.