Text document clustering based on frequent word sequences

International Conference on Information and Knowledge Management, Proceedings

Volumn , Issue , 2005, Pages 293-294

  Li, Yanjun ^a   Chung, Soon M ^a  

^a Wright State University   (United States)

Author keywords

Clustering; Frequent word sequences; Text documents; Web search

Indexed keywords

ALGORITHMS; DATABASE SYSTEMS; FORMAL LANGUAGES; INFORMATION RETRIEVAL; KNOWLEDGE ENGINEERING; PATTERN RECOGNITION; SEARCH ENGINES; VECTORS;

CLUSTERING; FREQUENT WORD SEQUENCES; TEXT DOCUMENTS; WEB SEARCH;

WORD PROCESSING;

EID: 33745770235     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1099554.1099633     Document Type: Conference Paper

References (6)

1. B. C. M. Fung, K. Wang, and M. Ester, "Hierarchical Document Clustering Using Frequent Itemsets," Proc. of SIAM Int'l Conf. on Data Mining, 2003.
2. High Accuracy Retrieval from Documents (HARD) Track of Text Retrieval Conference, 2004.
3. The Lemur Toolkit for Language Modeling and Information Retrieval, http://www-2.cs.emu.edu/~lemur/.
4. M. Steinbach, G. Karypis, and V. Kumar, "A Comparison of Document Clustering Techniques," KDD-2000 Workshop on Text Mining, 2000.
5. P. Weiner, "Linear Pattern Matching Algorithms," Proc. of the 14th Annual Symp. on Foundation of Computer Science, 1973, pp. 1-11.
6. O. Zamir and O. Etzioni, "Web Document Clustering: A Feasibility Demonstration," Proc. of Annual ACM SIGIR Conf. on Research and Development in Information Retrieval, 1998, pp. 46-54.