Incremental clustering of newsgroup articles

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

Volumn 4031 LNAI, Issue , 2006, Pages 332-341

  Hennig, Sascha ^a   Wurst, Michael ^a  

^a TU DORTMUND UNIVERSITY   (Germany)

Author keywords

Data mining; Internet applications; Knowledge management

Indexed keywords

CONSTRAINT THEORY; COSTS; DATA MINING; INFORMATION MANAGEMENT; INFORMATION RETRIEVAL SYSTEMS; INTERNET;

CLUSTERING TEXT DOCUMENTS; INCREMENTAL CLUSTERING; INTERNET APPLICATIONS; KNOWLEDGE MANAGEMENT;

ARTIFICIAL INTELLIGENCE;

EID: 33746210741     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11779568_37     Document Type: Conference Paper

References (11)

1. Jain, A.K., Murty, M.N., Flynn, P.J.: Data clustering - a review. ACM Computing Surveys 31 (1999)
2. Charikar, M., Chekuri, C., Feder, T., Motwani, R.: Incremental clustering and dynamic information retrieval. SIAM Journal on Computing 33 (2004)
3. Beil, F., Ester, M., Xu, X.: Frequent term-based text clustering. In: Proceedings of the International Conference on Knowledge Discovery and Data Mining. (2002)
4. Fung, B.C.M., Wang, K., Ester, M.: Hierarchical document clustering using frequent items. In: Proceedings of the SIAM International Conference on Data Mining. (2003)
5. Agrawal, R., Imielinskl, T., Swami, A.: Mining association rules between sets of items in large databases. In: Proceedings of the ACM SIGMOD International Conference on Management of Data. (1993)
6. Wang, K., Xu, C., Liu, B.: Clustering transactions using large items. In: Proceedings of the International Conceference on Information and Knowledge Management. (1999)
7. Konstan, J.A., Miller, B.N., Maltz, D., Herlocker, J.L., Gordon, L.R., Riedl, J.: GroupLens: Applying collaborative filtering to Usenet news. Communications of the ACM 40 (1997)
8. Bekkerman, R., El-Yaniv, R., McCallum, A.: Multi-way distributional clustering via pairwise interactions. In: Proceedings of the International Conference on Machine Learning. (2005)
9. Cohn, D., Caruana, R., McCallum, A.: Semi-supervised clustering with user feedback. Technical Report TR2003-1892, Cornell University (2000)
10. Finley, T., Joachims, T.: Supervised clustering with support vector machines. In: Proceedings of the International Conference on Machine Learning. (2005)
11. Hotho, A., Staab, S., Stumme, G.: Ontologies improve text document clustering. In: Proceedings of the International Conference on Data Mining. (2003)