Detecting the change of clustering structure in categorical data streams

Proceedings of the Sixth SIAM International Conference on Data Mining

Volumn 2006, Issue , 2006, Pages 504-508

  Chen, Keke ^a   Liu, Ling ^a  

^a GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER SCIENCE; DATABASE SYSTEMS; DECISION MAKING; HIERARCHICAL SYSTEMS; INFORMATION TECHNOLOGY; REAL TIME SYSTEMS;

CATEGORICAL DATA STREAMS; CLUSTERING INFORMATION; CLUSTERING STRUCTURES; HIERARCHICAL ENTROPY TREE STRUCTURE (HE-TREE);

DATA MINING;

EID: 33745471314     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1137/1.9781611972764.49     Document Type: Conference Paper

References (6)

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2. BARBARA, D., Li, Y., AND COUTO, J. Coolcat: an entropy-based algorithm for categorical clustering. Proc. of ACM Conf. on Information and Knowledge Mgt. (CIKM) (2002).
3. CHEN, K., AND Liu, L. The "best k" for entropy-based categorical clustering. Proc. of Intl. Conf. on Scientific and Statistical Database Management (SSDBM) (2005).
4. CHEN, K., AND Liu, L. iVIBRATE: Interactive visualization based framework for clustering large datasets. To appear in ACM Transaction on Information Systems (2006).
5. GUHA, S., MEYERSON, A., MISHRA, N., MOTWANI, R., AND O'CALLAGHAN, L. Clustering data streams: Theory and practice. IEEE Trans. on Knowledge and Data Eng. 15 (2003).
6. Li, T., MA, S., AND OGIHARA, M. Entropy-based criterion in categorical clustering. Proc. of Intl. Conf. on Machine Learning (ICML) (2004).