A tolerance rough set based overlapping clustering for the DBLP data

Proceedings - 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT 2010

Volumn , Issue , 2010, Pages 57-60

  Obadi, Gamila ^a   Dráždilová, Pavla ^a   Hlaváček, Lukaš ^a   Martinovič, Jan ^a   Snášel, Václav ^a  

^a VSB TECHNICAL UNIVERSITY OF OSTRAVA   (Czech Republic)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING METHODS; DATA COLLECTION; DATA SETS; FUZZY C MEAN; OVERLAPPING CLUSTERING; ROUGH SET; ROUGH-SET BASED;

ROUGH SET THEORY;

CLUSTER ANALYSIS;

EID: 78649822896     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WI-IAT.2010.286     Document Type: Conference Paper

References (28)

1. Z. Pawlak, Rough Sets: Theoretical Aspects of Reasoning about Data. Norwell, MA, USA: Kluwer Academic Publishers, 1992.
2. X. Wang, J. Yang, X. Teng, W. Xia, and R. Jensen, "Feature selection based on rough sets and particle swarm optimization," Pattern Recogn. Lett., vol. 28, no. 4, pp. 459-471, 2007.
3. H. Midelfart, J. Komorowski, K. Nørsett, F. Yadetie, A. K. Sandvik, and A. Laegreid, "Learning rough set classifiers from gene expressions and clinical data," Fundam. Inf., vol. 53, no. 2, pp. 155-183, 2002.
4. N. Shan, W. Ziarko, H. J. Hamilton, and N. Cercone, "Using rough sets as tools for knowledge discovery," in KDD, 1995, pp. 263-268.
5. J. Komorowski, Z. Pawlak, L. Polkowski, and A. Skowron, "Rough sets: A tutorial," 1998.
6. M. Ley, "The dblp computer science bibliography: Evolution, research issues, perspectives," in SPIRE 2002: Proceedings of the 9th International Symposium on String Processing and Information Retrieval. London, UK: Springer-Verlag, 2002, pp. 1-10.
7. URL, http://en.wikipedia.org/wiki/DBLP.
8. O. R. Zaiane, J. Chen, and R. Goebel, "Dbconnect: mining research community on dblp data," in WebKDD/SNA-KDD '07: Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis. New York, NY, USA: ACM, 2007, pp. 74-81.
9. R. Klamma, P. M. Cuong, and Y. Cao, "You never walk alone: Recommending academic events based on social network analysis," in Complex (1), 2009, pp. 657-670.
10. S. Chan, R. Pon, and A. Cardenas, "Visualization and clustering of author social networks," in Distributed Multimedia Systems Conference, 2006, pp. 174-180.
11. Y. Peng, G. Kou, and Y. Shi, "Recent trends in data mining(dm): Document clustering of dm publications," in International Conference on Service Systems and Service Management, vol. 2, 2006, pp. 1653-1659.
12. J. Sun, D. Tao, and C. Faloutsos, "Beyond streams and graphs: dynamic tensor analysis," in KDD '06: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining. New York, NY, USA: ACM, 2006, pp. 374-383.
13. Y. Sun, J. Han, P. Zhao, Z. Yin, H. Cheng, and T. Wu, "Rankclus: integrating clustering with ranking for heterogeneous information network analysis," in EDBT '09: Proceedings of the 12th International Conference on Extending Database Technology. New York, NY, USA: ACM, 2009, pp. 565-576.
14. T. Li, C. Ding, Y. Zhang, and B. Shao, "Knowledge transformation from word space to document space," in SIGIR '08: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval. New York, NY, USA: ACM, 2008, pp. 187-194.
15. F. Coaquira and E. Acuna, "Applications of rough sets theory in data preprocessing for knowledge discovery," in Proceedings of the World Congress on Engineering and Computer Science WCECS 2007, San Francisco, USA, 2007.
16. L. Shuai-dong and C. Shi-hong, "Clustering of web learners based on rough set," Wuhan University Journal of Natural Sciences, vol. 9, pp. 542-546, 2004.
17. F. Questier, I. Arnaut-Rollier, B. Walczak, and D. L. Massart, "Application of rough set theory to feature selection for unsupervised clustering," Chemometrics and Intelligent Laboratory Systems, vol. 63, no. 2, pp. 155 - 167, 2002. [Online]. Available: http://www.sciencedirect.com/ science/article/B6TFP-45VCHV5-1/2/9a6580c762bad40bf6371e3b95ec0439
18. D. Chen, D. wu Cui, C. xue Wang, and Z. rong Wang, "A rough set-based hierarchical clustering algorithm for categorical data," International Journal of Information Technology, vol. 12, pp. 149-159, 2006.
19. C. Bean and C. Kambhampati2, "Autonomous clustering using rough set theory," International Journal of Automation and Computing, vol. 5, pp. 90-102, 2008.
20. P. Lingras and C. West, "Interval set clustering of web users with rough k-means," J. Intell. Inf. Syst., vol. 23, no. 1, pp. 5-16, 2004.
21. S. K. De and P. R. Krishna, "Clustering web transactions using rough approximation," Fuzzy Sets and Systems, vol. 148, no. 1, pp. 131 - 138, 2004, web Mining Using Soft Computing. [Online]. Available: http://www. sciencedirect.com/science/article/B6V05-4C47NPP-7/2/ 08fd9f0da8ded7e7e801ecb7ae2a6938
22. J. W. Grzymala-busse and S. Siddhaye, "Rough set approaches to rule induction from incomplete data," in Proceedings the 10th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2004, pp. 923-930.
23. T.-P. Hong, L.-H. Tseng, and S.-L. Wang, "Learning rules from incomplete training examples by rough sets," Expert Systems with Applications, vol. 22, no. 4, pp. 285 - 293, 2002. [Online]. Available: http://www.sciencedirect.com/science/article/B6V03-454FD4K-1/2/ b783405e7d019a5d9ccc3f859eb6cc40
24. F. V. Nelwamondo and T. Marwala, "Rough sets computations to impute missing data," CoRR, vol. abs/0704.3635, 2007.
25. T. B. Ho and N. B. Nguyen, "Nonhierarchical document clustering based on a tolerance rough set model," International Journal of Intelligent Systems, vol. 17, pp. 199-212, 2002.
26. T. B. Ho, S. Kawasaki, and N. B. Nguyen, "Documents clustering using tolerance rough set model and its application to information retrieval," pp. 181-196, 2003.
27. G. Peters, "Some refinements of rough k-means clustering," Pattern Recogn., vol. 39, no. 8, pp. 1481-1491, 2006.
28. J. C. Bezdek, Pattern Recognition with Fuzzy Objective Function Algorithms. Norwell, MA, USA: Kluwer Academic Publishers, 1981.