A fuzzy hierarchical clustering method for clustering documents based on dynamic cluster centers

Journal of the Chinese Institute of Engineers, Transactions of the Chinese Institute of Engineers,Series A/Chung-kuo Kung Ch'eng Hsuch K'an

Volumn 30, Issue 1, 2007, Pages 169-172

  Chen, Shyi Ming ^a   Chen, Liang Yu ^a  

^a NATIONAL TAIWAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Taiwan)

Author keywords

Clustering accuracy rate; Dynamic document cluster centers; Fuzzy hierarchical clustering; Information retrieval; Inverse document frequency; Term frequency factor

Indexed keywords

HIERARCHICAL SYSTEMS; INFORMATION RETRIEVAL; INFORMATION RETRIEVAL SYSTEMS; NUMERICAL METHODS;

CLUSTERING ACCURACY RATES; DYNAMIC DOCUMENT CLUSTER CENTERS; FUZZY HIERARCHICAL CLUSTERING; INVERSE DOCUMENT FREQUENCIES; TERM FREQUENCY FACTORS;

FUZZY SETS;

EID: 33846799296     PISSN: 02533839     EISSN: 21587299     Source Type: Journal    
DOI: 10.1080/02533839.2007.9671241     Document Type: Article

References (16)

1. Baeza-Yates, R., and Ribeiro-Neto, B., 1999. Modern Information Retrieval, NY, USA:ACM Press.
2. Bezdek, J. C., 1980. “A Convergence Theorem for the Fuzzy ISODATA Clustering Algorithms,”. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2 (1):1–8.
3. Bezdek, J. C., 1981. Pattern Recognition with Fuzzy Objective Function Algorithms, Plenum NY, USA
4. Bezdek, J. C., Hathaway, R. J., Sabin, M. J., and Tucker, W. T., 1987. “Convergence Theory for Fuzzy C-Means:Counterexamples and Repairs,”. IEEE Transactions on Systems, Man, and Cybernetics, 17 (5):873–877.
5. Chen, L. Y., and Chen, S. M., “A New Fuzzy Hierarchical Clustering Method Based on Dynamic Cluster Centers,”. Proceeding of the 2003 Ninth Conference on Information Management Research. Changhua, Taiwan.
6. Chen, S. M., and Lin, Y. S., 2002. “A New Method for Fuzzy Query Processing in Relational Database Systems,”. Cybernetics and Systems:An International Journal, 33 (5):447–482.
7. Dave, R. N., and Sen, S., 2002. “Robust Fuzzy Clustering of Relational Data,”. IEEE Transactions on Fuzzy Systems, 10 (6):713–727.
8. Geva, A. B., 1999. “Hierarchical Unsupervised Fuzzy Clustering,”. IEEE Transactions on Fuzzy Systems, 7 (6):723–733.
9. Horng, Y. J., Chen, S. M., and Lee, C. H., “Fuzzy Information Retrieval Using Fuzzy Hierarchical Clustering and Fuzzy Inference Techniques,”. Proceedings of the 13th International Conference on Information Management. Taipei, Taiwan. Vol. 1, pp. 215–222. Republic of China.
10. Hunt, C., 1997. TCP/IP Network Administration, Sebastopol, CA, USA:O'Reilly.
11. Kaymak, U., and Setnes, M., 2002. “Fuzzy Clustering with Volume Prototypes and Adaptive Clustering Merging,”. IEEE Transactions on Fuzzy Systems, 10 (6):705–712.
12. Kraft, D. H., Chen, J., and Mikulcic, A., “Combining Fuzzy Clustering and Fuzzy Inferencing in Information Retrieval,”. Proceedings of the Ninth IEEE International Conference on Fuzzy Systems. San Antonio, TX, USA. Vol. 1, pp. 375–380.
13. Lin, K. I., and Kondadadi, R., “A Similarity-Based Soft Clustering Algorithm for Documents,”. Proceedings of the 7th International Conference on Database Systems for Advanced Applications. Hong Kong, China. pp. 40–47.
14. Ruspini, E., 1970. “Numerical Methods for Fuzzy Clustering,”. Information Sciences, 2:319–350.
15. Salton, G., 1971. The Smart Retrieval System - Experiments in Automatic Document Processing, Englewood Cliffs, NJ, USA:Prentice Hall.
16. A Subset of the Collection of the Research Reports of the National Science Council, Taiwan, http://fuzzylab.et.ntust.edu.tw/NSC-Report-Database/292documents.html (Data Source:http://sticnet. stic.gov.tw).