A metric cache for similarity search
Lucchese C., Perego R., Rabitti F., Falchi F., Orlando S.
Content Based Image Retrieval Cache
Similarity search in metric spaces is a general paradigm that can be used in several application elds. It can also be ef- fectively exploited in content-based image retrieval systems, which are shifting their target towards theWeb-scale dimen- sion. In this context, an important issue becomes the design of scalable solutions, which combine parallel and distributed architectures with caching at several levels. To this end, we investigate the design of a similarity cache that works in metric spaces. It is able to answer with exact and approximate results: even when an exact match is not present in cache, our cache may return an approximate re- sult set with quality guarantees. By conducting tests on a collection of one million high-quality digital photos, we show that the proposed caching techniques can have a signi cant impact on performance, like caching on text queries has been proved e ective for traditional Web search engines.
Source: Sixth Workshop on Large-Scale Distributed Systems for Information Retrieval, pp. 43–50, Napa Valley, California, US, 26-30 October 2008
Publisher: ACM Press, New York, USA
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@inproceedings{oai:it.cnr:prodotti:91816,
title = {A metric cache for similarity search},
author = {Lucchese C. and Perego R. and Rabitti F. and Falchi F. and Orlando S.},
publisher = {ACM Press, New York, USA},
doi = {10.1145/1458469.1458473},
booktitle = {Sixth Workshop on Large-Scale Distributed Systems for Information Retrieval, pp. 43–50, Napa Valley, California, US, 26-30 October 2008},
year = {2008}
}
0000-0001-6258-5313