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Soft Computing
Published in: Soft Computing 6/2015

01-06-2015 | Focus

Double-phase locality-sensitive hashing of neighborhood development for multi-relational data

Authors: Ping Ling, Xiangsheng Rong, Yongquan Dong, Guosheng Hao

Published in: Soft Computing | Issue 6/2015

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Abstract

Multi-relational (MR) data refer to the objects that involve multi-associated tables or a relational database, and they are widely used in diverse applications. In spite of rich achievements in concrete classification or regression tasks, a neighborhood development algorithm customized to MR data is still missing. The reason lies in the fact that MR data are high-dimensional and highly structured. To address these two difficulties, this paper presents a double-phase locality-sensitive hashing (DPLSH) algorithm to develop neighborhood for MR data. DPLSH consists of offline and online hashing schemas to draw and summarize local closeness information from each involved table. Based on the closeness information, three criteria of neighborhood development are proposed. DPLSH is encoded with parameterization heuristics to make the algorithm data adaptive and less costly. Extensive experiments indicate that for MR data, the quality of neighborhoods produced by DPLSH is better than its peers; besides, in common data environment, DPLSH also exhibits the competitive behaviors with the state of the art.
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Appendix
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Metadata
Title
Double-phase locality-sensitive hashing of neighborhood development for multi-relational data
Authors
Ping Ling
Xiangsheng Rong
Yongquan Dong
Guosheng Hao
Publication date
01-06-2015
Publisher
Springer Berlin Heidelberg
Published in
Soft Computing / Issue 6/2015
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-014-1343-4

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