E-stream: Evolution-based technique for stream clustering

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4632 LNAI, Issue , 2007, Pages 605-615

  Udommanetanakit, Komkrit ^a   Rakthanmanon, Thanawin ^a   Waiyamai, Kitsana ^a  

^a KASETSART UNIVERSITY   (Thailand)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTER ANALYSIS; INTRUSION DETECTION; MATHEMATICAL MODELS; REAL TIME SYSTEMS; DATA COMMUNICATION SYSTEMS;

DATA STREAMS; FRAUD DETECTION; SELF-EVOLUTION; ANALYSIS OF DATA; CLICKSTREAMS; CLUSTER MODELS; CURRENT DATA; DATA STREAM; NETWORK INTRUSION DETECTION; STREAM CLUSTERING;

CLUSTERING ALGORITHMS;

EID: 38049025951     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-73871-8_58     Document Type: Conference Paper

References (9)

1. Milenova, B.L., Campos, M.M.: Clustering Large Databases with Numeric and Nominial Values Using Orthogonal Projections. In: Proceedings of the 29th VLDB Conference (2003)
2. Aggarwal, C., Han, J., Wang, J., Yu, P.S.: A Framework for Projected Clustering of High Dimensional Data Streams. In: Proceeding of the 30th VLDB conference (2004)
3. Aggarwal, C., Han, J., Wang, J., Yu, P.S.: A Framework for Clustering Evolving Data Streams. In: Proceeding of the 29th VLDB conference (2003)
4. Barbara, D.: Requirements for Clustering Data Streams. In: SIGKDD Explorations (2002)
5. Gaber, M.M., Zaslavsky, A., Krishnaswmy, S.: Mining Data Streams: A Review. In: SIGMOD Record, vol. 34(2) (June 2005)
6. Oh, S., Kang, J., Byun, Y., Park, G., Byun, S.: Intrusion Detection based on Clustering a Data Stream. In: Proceedings of the 2005 Third ACIS International Conference on Software Engineering Research, Management and Applications (2005)
7. Guha, S., Meyerson, A., Mishra, N., Motwani, R., O'Callaghan, L.: Clustering Data Streams: Theory and Practice. TKDE special issue on clustering 15 (2003)
8. Song, M., Wang, H.: Highly Efficient Incremental Estimation of Gaussian Mixture Models for Online Data Stream Clustering. In: SPIE Conference on Intelligent Computing: Theory And Application III (2005)
9. Zhang, T., Ramakhrisnan, R., Livny, M.: BIRCH: An Efficient Data Clustering Method for Very Large Databases. In: Proc. ACM SIGMOD Int. Conf. Management of Data (1996)