Double-phase locality-sensitive hashing of neighborhood development for multi-relational data
| LEADER | caa a22 4500 | ||
|---|---|---|---|
| 001 | 605468591 | ||
| 003 | CHVBK | ||
| 005 | 20210128100317.0 | ||
| 007 | cr unu---uuuuu | ||
| 008 | 210128e20150601xx s 000 0 eng | ||
| 024 | 7 | 0 | |a 10.1007/s00500-014-1343-4 |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s00500-014-1343-4 | ||
| 245 | 0 | 0 | |a Double-phase locality-sensitive hashing of neighborhood development for multi-relational data |h [Elektronische Daten] |c [Ping Ling, Xiangsheng Rong, Yongquan Dong, Guosheng Hao] |
| 520 | 3 | |a 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. | |
| 540 | |a Springer-Verlag Berlin Heidelberg, 2014 | ||
| 690 | 7 | |a Multi-relational data |2 nationallicence | |
| 690 | 7 | |a Neighborhood development |2 nationallicence | |
| 690 | 7 | |a Locality-sensitive hashing |2 nationallicence | |
| 690 | 7 | |a Double-phase approach |2 nationallicence | |
| 690 | 7 | |a Parameterization |2 nationallicence | |
| 700 | 1 | |a Ling |D Ping |u College of Computer Science and Technology, Jiangsu Normal University, 221116, Xuzhou, China |4 aut | |
| 700 | 1 | |a Rong |D Xiangsheng |u Department of Training, Air Force Logistics of P. L. A, 221000, Xuzhou, China |4 aut | |
| 700 | 1 | |a Dong |D Yongquan |u College of Computer Science and Technology, Jiangsu Normal University, 221116, Xuzhou, China |4 aut | |
| 700 | 1 | |a Hao |D Guosheng |u College of Computer Science and Technology, Jiangsu Normal University, 221116, Xuzhou, China |4 aut | |
| 773 | 0 | |t Soft Computing |d Springer Berlin Heidelberg |g 19/6(2015-06-01), 1553-1565 |x 1432-7643 |q 19:6<1553 |1 2015 |2 19 |o 500 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s00500-014-1343-4 |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s00500-014-1343-4 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Ling |D Ping |u College of Computer Science and Technology, Jiangsu Normal University, 221116, Xuzhou, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Rong |D Xiangsheng |u Department of Training, Air Force Logistics of P. L. A, 221000, Xuzhou, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Dong |D Yongquan |u College of Computer Science and Technology, Jiangsu Normal University, 221116, Xuzhou, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Hao |D Guosheng |u College of Computer Science and Technology, Jiangsu Normal University, 221116, Xuzhou, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Soft Computing |d Springer Berlin Heidelberg |g 19/6(2015-06-01), 1553-1565 |x 1432-7643 |q 19:6<1553 |1 2015 |2 19 |o 500 | ||