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https://doi.org/10.1007/978-3-642-12026-8_4
DC Field | Value | |
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dc.title | iDISQUE: Tuning high-dimensional similarity queries in DHT networks | |
dc.contributor.author | Zhang, X. | |
dc.contributor.author | Shou, L. | |
dc.contributor.author | Tan, K.-L. | |
dc.contributor.author | Chen, G. | |
dc.date.accessioned | 2013-07-04T08:44:44Z | |
dc.date.available | 2013-07-04T08:44:44Z | |
dc.date.issued | 2010 | |
dc.identifier.citation | Zhang, X.,Shou, L.,Tan, K.-L.,Chen, G. (2010). iDISQUE: Tuning high-dimensional similarity queries in DHT networks. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 5981 LNCS (PART 1) : 19-33. ScholarBank@NUS Repository. <a href="https://doi.org/10.1007/978-3-642-12026-8_4" target="_blank">https://doi.org/10.1007/978-3-642-12026-8_4</a> | |
dc.identifier.isbn | 3642120253 | |
dc.identifier.issn | 03029743 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/42155 | |
dc.description.abstract | In this paper, we propose a fully decentralized framework called iDISQUE to support tunable approximate similarity query of high dimensional data in DHT networks. The iDISQUE framework utilizes a distributed indexing scheme to organize data summary structures called iDisques, which describe the cluster information of the data on each peer. The publishing process of iDisques employs a locality-preserving mapping scheme. Approximate similarity queries can be resolved using the distributed index. The accuracy of query results can be tuned both with the publishing and query costs. We employ a multi-probe technique to reduce the index size without compromising the effectiveness of queries. We also propose an effective load-balancing technique based on multi-probing. Experiments on real and synthetic datasets confirm the effectiveness and efficiency of iDISQUE. © Springer-Verlag Berlin Heidelberg 2010. | |
dc.description.uri | http://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/978-3-642-12026-8_4 | |
dc.source | Scopus | |
dc.type | Conference Paper | |
dc.contributor.department | COMPUTER SCIENCE | |
dc.description.doi | 10.1007/978-3-642-12026-8_4 | |
dc.description.sourcetitle | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | |
dc.description.volume | 5981 LNCS | |
dc.description.issue | PART 1 | |
dc.description.page | 19-33 | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Staff Publications |
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