Using clustering to enhance text classification

Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR'07

Volumn , Issue , 2007, Pages 805-806

  Kyriakopoulou, Antonia ^a   Kalamboukis, Theodore ^a  

^a ATHENS UNIVERSITY OF ECONOMICS AND BUSINESS   (Greece)

Author keywords

Clustering; Text classification

Indexed keywords

CLASSIFICATION (OF INFORMATION); CLUSTERING ALGORITHMS; DATABASE SYSTEMS; LEARNING SYSTEMS; PROBLEM SOLVING; TEXT PROCESSING;

TEXT CLASSIFICATION; TRAINING SETS;

INFORMATION RETRIEVAL;

EID: 36448989607     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1277741.1277918     Document Type: Conference Paper

References (7)

1. R. Bekkerman, R. El-Yaniv, and Y. Winter. Distributional word clusters vs. words for text categorization. Journal of Machine Learning Research, 3:1183-1208, 2003.
2. T. Joachims. Transductive inference for text classication using support vector machines. In 16th International Conference on Machine Learning Proceedings, pages 200-209, 1999.
3. G. Karypis. Cluto a clustering toolkit. Technical Report 02-017, 2002.
4. A. Kyriakopoulou and T. Kalamboukis. Text classification using clustering. In ECML-PKDD Discovery Challenge Workshop Proceedings, 2006.
5. B. Raskutti, H. Ferr, and A. Kowalczyk. Using unlabeled data for text classification through addition of cluster parameters. In 9th International Conference on Machine Learning ICML Proceedings, 2002.
6. G. Salton and M. McGill. Introduction to Modern Information Retrieval. New York: McGraw-Hill, 1983.
7. H. Zeng, X. Wang, Z. Chen, H. Lu, and W. Ma. Cbc: Clustering based text classification requiring minimal labeled data. In 3rd IEEE International Conference on Data Mining Proceedings, 2003.