Propagating Expiration Decisions in a Search Engine Result Cache

Sazoglu, Fethi Burak
Altıngövde, İsmail Sengör
Ozcan, Rifat
Barla Cambazoglu, B.
Detecting stale queries in a search engine result cache is an important problem. In this work, we propose a mechanism that propagates the expiration decision for a query to similar queries in the cache to re-adjust their time-to-live values.


Static query result caching revisited
Ozcan, Rifat; Altıngövde, İsmail Sengör; Ulusoy, Özgür (2008-12-15)
Query result caching is an important mechanism for search engine efficiency. In this study, we first review several query features that are used to determine the contents of a static result cache. Next, we introduce a new feature that more accurately represents the popularity of a query by measuring the stability of query frequency over a set of time intervals. Experimental results show that this new feature achieves hit ratios better than those of the previously proposed features.
Characterizing web search queries that match very few or no results
Altıngövde, İsmail Sengör; Cambazoglu, Berkant Barla; Ozcan, Rifat; Sarigil, Erdem; Ulusoy, Özgür (2012-12-19)
Despite the continuous efforts to improve the web search quality, a non-negligible fraction of user queries end up with very few or even no matching results in leading web search engines. In this work, we provide a detailed characterization of such queries based on an analysis of a real-life query log. Our experimental setup allows us to characterize the queries with few/no results and compare the mechanisms employed by the major search engines in handling them.
Evolution of web search results within years
Altıngövde, İsmail Sengör; Ulusoy, Özgür (2011-01-01)
We provide a first large-scale analysis of the evolution of query results obtained from a real search engine at two distant points in time, namely, in 2007 and 2010, for a set of 630,000 real queries.
Probabilistic matrix factorization based collaborative filtering with implicit trust derived from review ratings information
Ercan, Eda; Taşkaya Temizel, Tuğba; Department of Information Systems (2010)
Recommender systems aim to suggest relevant items that are likely to be of interest to the users using a variety of information resources such as user profiles, trust information and users past predictions. However, typical recommender systems suffer from poor scalability, generating incomprehensible and not useful recommendations and data sparsity problem. In this work, we have proposed a probabilistic matrix factorization based local trust boosted recommendation system which handles data sparsity, scalabil...
On the Efficiency of Selective Search
Hafizoglu, Fatih; Kucukoglu, Emre Can; Altıngövde, İsmail Sengör (2017-04-13)
Our work shows that the query latency for selective search over a topically partitioned collection can be reduced by up to 55%. We achieve this by physically storing the documents in each topical cluster across all shards and building a cluster-skipping index at each shard. Our approach also achieves uniform load balance among the shards.
Citation Formats
F. B. Sazoglu, İ. S. Altıngövde, R. Ozcan, B. Barla Cambazoglu, and Ö. ULUSOY, “Propagating Expiration Decisions in a Search Engine Result Cache,” 2015, Accessed: 00, 2020. [Online]. Available: