Incremental semi-supervised clustering ensemble for high dimensional data clustering

Zhiwen Yu, Peinan Luo, Si Wu, Guoqiang Han, Jia You, Hareton Leung, Hau San Wong, Jun Zhang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

6 Citations (Scopus)

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.
Original languageEnglish
Title of host publication2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016
PublisherIEEE
Pages1484-1485
Number of pages2
ISBN (Electronic)9781509020195
DOIs
Publication statusPublished - 22 Jun 2016
Event32nd IEEE International Conference on Data Engineering, ICDE 2016 - Helsinki, Finland
Duration: 16 May 201620 May 2016

Conference

Conference32nd IEEE International Conference on Data Engineering, ICDE 2016
CountryFinland
CityHelsinki
Period16/05/1620/05/16

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Computer Graphics and Computer-Aided Design
  • Computer Networks and Communications
  • Information Systems
  • Information Systems and Management

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