Incremental semi-supervised clustering ensemble for high dimensional data clustering
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yu, Zhiwen | - |
dc.contributor.author | Luo, Peinan | - |
dc.contributor.author | Wu, Si | - |
dc.contributor.author | Han, Guoqiang | - |
dc.contributor.author | You, Jane | - |
dc.contributor.author | Leung, Hareton | - |
dc.contributor.author | Wong, Hau-San | - |
dc.contributor.author | Zhang, Jun | - |
dc.date.accessioned | 2023-12-12T12:30:38Z | - |
dc.date.available | 2023-12-12T12:30:38Z | - |
dc.date.issued | 2016-06 | - |
dc.identifier.issn | 1084-4627 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/116318 | - |
dc.description.abstract | Recently, cluster ensemble approaches have gained more and more attention [1]-[2], due to useful applications in the areas of pattern recognition, data mining, bioinformatics, and so on. When compared with traditional single clustering algorithms, cluster ensemble approaches are able to integrate multiple clustering solutions obtained from different data sources into a unified solution, and provide a more robust, stable and accurate final result. © 2016 IEEE. | - |
dc.format.extent | 2 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | Incremental semi-supervised clustering ensemble for high dimensional data clustering | - |
dc.type | Article | - |
dc.publisher.location | 미국 | - |
dc.identifier.doi | 10.1109/ICDE.2016.7498386 | - |
dc.identifier.scopusid | 2-s2.0-84980371925 | - |
dc.identifier.wosid | 000382554200163 | - |
dc.identifier.bibliographicCitation | 2016 IEEE 32nd International Conference on Data Engineering (ICDE), pp 1484 - 1485 | - |
dc.citation.title | 2016 IEEE 32nd International Conference on Data Engineering (ICDE) | - |
dc.citation.startPage | 1484 | - |
dc.citation.endPage | 1485 | - |
dc.type.docType | Conference paper | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | sci | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Theory & Methods | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/7498386 | - |
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