Median evidential c-means algorithm and its application to community detection

Knowledge-Based Systems

Volumn 74, Issue , 2015, Pages 69-88

  Zhou, Kuang ^a,b   Martin, Arnaud ^b   Pan, Quan ^a   Liu, Zhun Ga ^a  

^a NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

^b CAMPUS DE BEAULIEU   (France)

Author keywords

Belief function theory; Community detection; Credal partition; Imprecise communities; Median clustering

Indexed keywords

ALGORITHMS; UNCERTAINTY ANALYSIS;

BELIEF FUNCTION THEORY; COMMUNITY DETECTION; MEDIAN CLUSTERING; METRIC SPACE EMBEDDING; PRE-MATURE CONVERGENCES; PROTOTYPE SELECTION SCHEME; PROTOTYPE-BASED CLUSTERING; SYNTHETIC AND REAL DATA;

POPULATION DYNAMICS;

EID: 84926155968     PISSN: 09507051     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.knosys.2014.11.010     Document Type: Article

References (50)

1. B. Amiri, L. Hossain, J.W. Crawford, R.T. Wigand, Community detection in complex networks: multi-objective enhanced firefly algorithm, Knowl.-Based Syst. 46 (2013) 1-11.
2. D. Arthur, S. Vassilvitskii, κ-means++: the advantages of careful seeding, in: Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms, Society for Industrial and Applied Mathematics, 2007, pp. 1027-1035.
3. J.C. Bezdek, Pattern Recognition with Fuzzy Objective Function Algorithms, Kluwer Academic Publishers., 1981.
4. V.D. Blondel, J.-L. Guillaume, R. Lambiotte, E. Lefebvre, Fast unfolding of communities in large networks, J. Stat. Mech.: Theory Exp. 2008 (10) (2008) P10008.
5. G. Bordogna, G. Pasi, A quality driven hierarchical data divisive soft clustering for information retrieval, Knowl.-Based Syst. 26 (2012) 9-19.
6. C. Borgelt, Prototype-based classification and clustering, Ph.D. thesis, Ottovon-Guericke-Universität Magdeburg, Universitätsbibliothek, 2006.
7. A. Clauset, M.E. Newman, C. Moore, Finding community structure in very large networks, Phys. Rev. E 70 (6) (2004) 066111.
8. M. Cottrell, B. Hammer, A. Hasenfuß, T. Villmann, Batch and median neural gas, Neural Netw. 19 (6) (2006) 762-771.
9. T. Denoeux, M.-H. Masson, EVCLUS: evidential clustering of proximity data, IEEE Trans. Syst. Man Cybernet. Part B: Cybernet. 34 (1) (2004) 95-109.
10. J. Duch, A. Arenas, Community detection in complex networks using extremal optimization, Phys. Rev. E 72 (2) (2005) 027104.
11. J.C. Dunn, A fuzzy relative of the isodata process and its use in detecting compact well-separated clusters, J. Cybernet. 3 (1973) 32-57.
12. R.A. Fisher, The use of multiple measurements in taxonomic problems, Ann. Eugen. 7 (2) (1936) 179-188.
13. S. Fortunato, Community detection in graphs, Phys. Rep. 486 (3) (2010) 75-174.
14. S. Fortunato, M. Barthelemy, Resolution limit in community detection, Proc. Natl. Acad. Sci. 104 (1) (2007) 36-41.
15. C. Gao, D. Wei, Y. Hu, S. Mahadevan, Y. Deng, A modified evidential methodology of identifying influential nodes in weighted networks, Physica A: Stat. Mech. Its Appl. 392 (21) (2013) 5490-5500.
16. T. Geweniger, D. Zülke, B. Hammer, T. Villmann, Median fuzzy c-means for clustering dissimilarity data, Neurocomputing 73 (7) (2010) 1109-1116.
17. T. Graepel, R. Herbrich, P. Bollmann-Sdorra, K. Obermayer, Classification on pairwise proximity data, Adv. Neural Inform. Process. Syst. (1999) 438-444.
18. B. Hammer, A. Hasenfuss, Relational neural gas, in: KI 2007: Advances in Artificial Intelligence, Springer, 2007, pp. 190-204.
19. R.J. Hathaway, J.C. Bezdek, Nerf c-means: non-euclidean relational fuzzy clustering, Pattern Recogn. 27 (3) (1994) 429-437.
20. R.J. Hathaway, J.W. Davenport, J.C. Bezdek, Relational duals of the c-means clustering algorithms, Pattern Recogn. 22 (2) (1989) 205-212.
21. T. Havens, J. Bezdek, C. Leckie, K. Ramamohanarao, M. Palaniswami, A soft modularity function for detecting fuzzy communities in social networks, IEEE Trans. Fuzzy Syst. 21 (6) (2013) 1170-1175.
22. T. Hofmann, J.M. Buhmann, Pairwise data clustering by deterministic annealing, IEEE Trans. Pattern Anal. Machine Intell. 19 (1) (1997) 1-14.
23. Y. Hu, M. Li, P. Zhang, Y. Fan, Z. Di, Community detection by signaling on complex networks, Phys. Rev. E 78 (1) (2008) 016115.
24. M.Z. Islam, L. Brankovic, Privacy preserving data mining: a noise addition framework using a novel clustering technique, Knowl.-Based Syst. 24 (8) (2011) 1214-1223.
25. A.K. Jain, Data clustering: 50 years beyond k-means, Pattern Recogn. Lett. 31 (8) (2010) 651-666.
26. Y. Jiang, C. Jia, J. Yu, An efficient community detection method based on rank centrality, Physica A: Stat. Mech. Its Appl. (2012).
27. A. Lancichinetti, S. Fortunato, J. Kertész, Detecting the overlapping and hierarchical community structure in complex networks, New J. Phys. 11 (3) (2009) 033015.
28. A. Lancichinetti, S. Fortunato, F. Radicchi, Benchmark graphs for testing community detection algorithms, Phys. Rev. E 78 (4) (2008) 046110.
29. J. Liu, T. Liu, Detecting community structure in complex networks using simulated annealing with k-means algorithms, Physica A: Stat. Mech. Its Appl. 389 (11) (2010) 2300-2309.
30. Z.-G. Liu, Q. Pan, J. Dezert, Evidential classifier for imprecise data based on belief functions, Knowl.-Based Syst. 52 (2013) 246-257.
31. A. Martin, I. Quidu, Decision support with belief functions theory for seabed characterization, in: 2008 11th International Conference on Information Fusion, IEEE, 2008, pp. 1-8.
32. M.-H. Masson, T. Denoeux, ECM: an evidential version of the fuzzy c-means algorithm, Pattern Recogn. 41 (4) (2008) 1384-1397.
33. M.-H. Masson, T. Denoeux, RECM: relational evidential c-means algorithm, Pattern Recogn. Lett. 30 (11) (2009) 1015-1026.
34. M. Mendes, L. Sacks, Evaluating fuzzy clustering for relevance-based information access, The 12th IEEE International Conference on Fuzzy Systems, 2003 (FUZZ'03), vol. 1, IEEE, 2003, pp. 648-653.
35. M.E. Newman, M. Girvan, Finding and evaluating community structure in networks, Phys. Rev. E 69 (2) (2004) 026113.
36. U.N. Raghavan, R. Albert, S. Kumara, Near linear time algorithm to detect community structures in large-scale networks, Phys. Rev. E 76 (3) (2007) 036106.
37. M. Sales-Pardo, R. Guimera, A.A. Moreira, L.A.N. Amaral, Extracting the hierarchical organization of complex systems, Proc. Natl. Acad. Sci. 104 (39) (2007) 15224-15229.
38. J. Schubert, Clustering belief functions based on attracting and conflicting metalevel evidence using potts spin mean field theory, Inform. Fusion 5 (4) (2004) 309-318.
39. P. Smets, Decision making in the TBM: the necessity of the pignistic transformation, Int. J. Approx. Reason. 38 (2) (2005) 133-147.
40. S. Smyth, S. White, A spectral clustering approach to finding communities in graphs, in: Proceedings of the 5th SIAM International Conference on Data Mining, 2005, pp. 76-84.
41. M. Tabassian, R. Ghaderi, R. Ebrahimpour, Combining complementary information sources in the Dempster-Shafer framework for solving classification problems with imperfect labels, Knowl.-Based Syst. 27 (2012) 92-102.
42. M. Tasgin, A. Herdagdelen, H. Bingol, Community detection in complex networks using genetic algorithms, arXiv preprint arXiv:0711.0491, 2007.
43. B. Yang, J. Di, J. Liu, D. Liu, Hierarchical community detection with applications to real-world network analysis, Data Knowl. Eng. 83 (2013) 20-38.
44. X. Yang, G. Zhang, J. Lu, J. Ma, A kernel fuzzy c-means clustering-based fuzzy support vector machine algorithm for classification problems with outliers or noises, IEEE Trans. Fuzzy Syst. 19 (1) (2011) 105-115.
45. W.W. Zachary, An information flow model for conflict and fission in small groups, J. Anthropol. Res. (1977) 452-473.
46. S. Zhang, R.-S. Wang, X.-S. Zhang, Identification of overlapping community structure in complex networks using fuzzy c-means clustering, Physica A: Stat. Mech. Its Appl. 374 (1) (2007) 483-490.
47. W. Zhang, T. Yoshida, X. Tang, Q. Wang, Text clustering using frequent itemsets, Knowl.-Based Syst. 23 (5) (2010) 379-388.
48. X. Zhang, J. Zhu, Q. Wang, H. Zhao, Identifying influential nodes in complex networks with community structure, Knowl.-Based Syst. 42 (2013) 74-84.
49. H. Zhou, Distance, dissimilarity index, and network community structure, Phys. Rev. E 67 (6) (2003) 061901.
50. K. Zhou, A. Martin, Q. Pan, Evidential communities for complex networks, in: Information Processing and Management of Uncertainty in Knowledge-Based Systems, Springer, 2014, pp. 557-566.