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The Impact of Using Combinatorial Optimisation for Static Caching of Posting Lists

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Information Retrieval Technology (AIRS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9460))

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Abstract

Caching posting lists can reduce the amount of disk I/O required to evaluate a query. Current methods use optimisation procedures for maximising the cache hit ratio. A recent method selects posting lists for static caching in a greedy manner and obtains higher hit rates than standard cache eviction policies such as LRU and LFU. However, a greedy method does not formally guarantee an optimal solution. We investigate whether the use of methods guaranteed, in theory, to find an approximately optimal solution would yield higher hit rates. Thus, we cast the selection of posting lists for caching as an integer linear programming problem and perform a series of experiments using heuristics from combinatorial optimisation (CCO) to find optimal solutions. Using simulated query logs we find that CCO yields comparable results to a greedy baseline using cache sizes between 200 and 1000 MB, with modest improvements for queries of length two to three.

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Notes

  1. 1.

    http://lemurproject.org/clueweb09/anchortext-querylog/.

  2. 2.

    https://projects.coin-or.org/SYMPHONY.

  3. 3.

    http://lpsolve.sourceforge.net/5.5/.

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Correspondence to Casper Petersen .

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Petersen, C., Simonsen, J.G., Lioma, C. (2015). The Impact of Using Combinatorial Optimisation for Static Caching of Posting Lists. In: Zuccon, G., Geva, S., Joho, H., Scholer, F., Sun, A., Zhang, P. (eds) Information Retrieval Technology. AIRS 2015. Lecture Notes in Computer Science(), vol 9460. Springer, Cham. https://doi.org/10.1007/978-3-319-28940-3_36

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  • DOI: https://doi.org/10.1007/978-3-319-28940-3_36

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28939-7

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