Genetic-guided semi-supervised clustering algorithm with instance-level constraints

Yi HONG, Hui XIONG, Sam KWONG, Qingsheng REN

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

11 Citations (Scopus)


Semi-supervised clustering with instance-level constraints is one of the most active research topics in the areas of pattern recognition, machine learning and data mining. Several recent studies have shown that instance-level constraints can significantly increase accuracies of a variety of clustering algorithms. However, instance-level constraints may split the search space of the optimal clustering solution into pieces, thus significantly compound the difficulty of the search task. This paper explores a genetic approach to solve the problem of semi-supervised clustering with instance-level constraints. In particular, a novel semi-supervised clustering algorithm with instance-level constraints, termed as the hybrid geneticguided semi-supervised clustering algorithm with instancelevel constraints (Cop-HGA), is proposed. Cop-HGA uses a hybrid genetic algorithm to perform the search task of a high quality clustering solution that is able to draw a good balance between predefined clustering criterion and available instance-level background knowledge. The effectiveness of Cop-HGA is confirmed by experimental results on several real data sets with artificial instance-level constraints. Copyright 2008 ACM.
Original languageEnglish
Title of host publicationGECCO'08: Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation 2008
EditorsMaarten KEIJZER
PublisherAssociation for Computing Machinery (ACM)
Number of pages8
ISBN (Print)9781605581309
Publication statusPublished - Jul 2008
Externally publishedYes
Event10th Annual Genetic and Evolutionary Computation Conference - Atlanta, United States
Duration: 12 Jul 200816 Jul 2008


Conference10th Annual Genetic and Evolutionary Computation Conference
Abbreviated titleGECCO 2008
Country/TerritoryUnited States


  • Genetic algorithms
  • Semi-supervised clustering


Dive into the research topics of 'Genetic-guided semi-supervised clustering algorithm with instance-level constraints'. Together they form a unique fingerprint.

Cite this