Text document clustering based on the modifying relations

Proceedings - International Conference on Computer Science and Software Engineering, CSSE 2008

Volumn 1, Issue , 2008, Pages 256-259

  Weixin, Tian ^a,b   Fuxi, Zhu ^a  

^a WUHAN UNIVERSITY   (China)

^b CHINA THREE GORGES UNIVERSITY   (China)

Author keywords

Clustering; Document representaion; Modifying relation

Indexed keywords

AGGLOMERATIVE HIERARCHICAL CLUSTERING; CLUSTERING; DOCUMENT REPRESENTAION; EFFICIENT METHODS; FEATURE SETS; MODIFYING RELATION; SIMILARITY MEASURES; TEXT DOCUMENTS;

COMPUTERS; FEATURE EXTRACTION; INFORMATION RETRIEVAL; KNOWLEDGE MANAGEMENT; SOFTWARE ENGINEERING; TEXT PROCESSING;

CLUSTERING ALGORITHMS;

EID: 61849174742     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CSSE.2008.1545     Document Type: Conference Paper

References (12)

1. F. Beil, M. Ester, X. Xu. Frequent term-based text clustering, in: Proceedings of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2002:436-442.
2. Dexi Liu, Yan Xiang He, Donghong Ji, Hua Yang. Multi-Document Summarization Based On BE-Vector Clustering. CICLing 2006, Lecture Notes in Computer Science, 2006(3878):470-479.
3. C. J. van Rijsbergen, Information Retrieval, 2nd ed., Buttersworth, London, 1979.
4. Eduard Hovy, Chin-Yew Lin, Liang Zhoujunichi Funkumoto. Basic Elements. Technical Report, http://www.isi.edu/~cyl/BE/index.html.
5. A. Hotho, S. Staab, G. Stumme, Ontologies improve text document clustering, in: Proceedings of the 3rd IEEE International Conference on Data Mining, 2003, pp. 541-544.
6. A. K. Jain, M. N. Murty & P. J. Flynn. Data Clustering:A Review, ACM Computing Surveys, (1999):264-323.
7. Miyamoto. Fuzzy multisets and fuzzy clustering of documents. In Proceedings of the IEEE International Conference on Fuzzy Systems, FUZZ-IEEE,(2001).
8. Ridvan Saraçoǧlu, Kemal Tütüncü, Novruz Allahverdi. A fuzzy clustering approach for finding similar documents using a novel similarity measure, Expert Systems with Applications, 2007, 33(3): 600-605.
9. M. Steinbach, G. Karypis, V. Kumar. A comparison of document clustering techniques, KDD-2000 Workshop on Text Mining, (2000).
10. Z. Volkovich, V Kirzhner, A. Bolshoy, E. Nevo, A. Korol. The method of N-grams in large-scale clustering of DNA texts, Pattern Recognition, 2005, 38(11):1902-1912.
11. Widyantoro, D. H., & Yen, J. A fuzzy similarity approach in text classification task, IEEE (2000).
12. Yanjun Li, Soon M. Chung, John D. Holt. Text document clustering based on frequent word meaning sequences, Data & Knowledge Engineering, 2008, 64(1):381-404.