Towards supporting expert evaluation of clustering results using a data mining process model

Kweku-Muata Osei-Bryson

doi:10.1016/j.ins.2009.09.019

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Towards supporting expert evaluation of clustering results using a data mining process model

Kweku-Muata Osei-Bryson

Year: 2009 Journal: Information Sciences Vol: 180 (3)Pages: 414-431 Publisher: Elsevier BV

DOI: 10.1016/j.ins.2009.09.019

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Keywords:

Cluster analysis Computer science Data mining Process (computing) Correlation clustering Consensus clustering CURE data clustering algorithm Artificial intelligence Machine learning Set (abstract data type) Canopy clustering algorithm Data stream clustering Segmentation Domain (mathematical analysis) Constrained clustering Fuzzy clustering Mathematics

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Advanced Clustering Algorithms Research

Physical Sciences → Computer Science → Artificial Intelligence

Data Mining Algorithms and Applications

Physical Sciences → Computer Science → Information Systems

Data Management and Algorithms

Physical Sciences → Computer Science → Signal Processing

Towards supporting expert evaluation of clustering results using a data mining process model

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