KYSELÁK, Martin, David NOVÁK and Pavel ZEZULA. Stabilizing the Recall in Similarity Search. In Alfredo Ferro. Fourth International Conference on Similarity Search and Applications, SISAP 2011. New York: ACM Press, 2011, p. 59-66. ISBN 978-1-4503-0795-6. Available from: https://dx.doi.org/10.1145/1995412.1995422.
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Basic information
Original name Stabilizing the Recall in Similarity Search
Name in Czech Stabilizace kvality v podobnost
Authors KYSELÁK, Martin (203 Czech Republic, guarantor, belonging to the institution), David NOVÁK (203 Czech Republic, belonging to the institution) and Pavel ZEZULA (203 Czech Republic, belonging to the institution).
Edition New York, Fourth International Conference on Similarity Search and Applications, SISAP 2011, p. 59-66, 8 pp. 2011.
Publisher ACM Press
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Italy
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
RIV identification code RIV/00216224:14330/11:00073202
Organization unit Faculty of Informatics
ISBN 978-1-4503-0795-6
Doi http://dx.doi.org/10.1145/1995412.1995422
Keywords in English locality-sensitive hashing; metric space; similarity search; recall; stability;
Tags DISA
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 1/4/2015 09:00.
Abstract
The recent techniques for approximate similarity search focus on optimizing answer precision/recall and they typically improve the average of these measures over a set of sample queries. However, according to our observation, the recall for particular indexes and queries can fluctuate considerably. In order to stabilize the recall, we propose a query-evaluation model that exploits several variants of the search index. This approach is applicable to a signicant subset of current approximate methods with a focus on techniques based purely on metric postulates. Applying this approach to the M-Index structure, we perform extensive measurements on large datasets and we show that this approach has a positive impact on the recall stability and it suppresses the most unsatisfactory cases. Further, the results indicate that the proposed approach can also increase the general average recall for given overall search costs.
Links
GAP103/10/0886, research and development projectName: Vizuální vyhledávání obrázků na Webu (Acronym: VisualWeb)
Investor: Czech Science Foundation, Content-based Image Retrieval on the Web Scale
GA201/09/0683, research and development projectName: Vyhledávání v rozsáhlých multimediálních databázích
Investor: Czech Science Foundation, Similarity Searching in Very Large Multimedia Databases
GPP202/10/P220, research and development projectName: Podobnostní vyhledávání s konstantní škálovatelností (Acronym: SIM-SCALE)
Investor: Czech Science Foundation
VF20102014004, research and development projectName: Multimediální analýza (Acronym: Multimediální analýza)
Investor: Ministry of the Interior of the CR
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