A metric cache for similarity search

32Citations
Citations of this article
12Readers
Mendeley users who have this article in their library.
Get full text

Abstract

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 effective for traditional Web search engines. Copyright 2008 ACM.

Cite

CITATION STYLE

APA

Falchi, F., Lucchese, C., Perego, R., Rabitti, F., & Orlando, S. (2008). A metric cache for similarity search. In International Conference on Information and Knowledge Management, Proceedings (pp. 43–50). https://doi.org/10.1145/1458469.1458473

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free