Seed-Centric approaches for community detection in complex networks

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8531 LNCS, Issue , 2014, Pages 197-208

  Kanawati, Rushed ^a  

^a UNIVERSITÉ PARIS 13   (France)

Author keywords

Community detection; complex networks; seed centric algorithms

Indexed keywords

COMPLEX NETWORKS; POPULATION DYNAMICS;

COMMUNITY CONSTRUCTIONS; COMMUNITY DETECTION; EMERGING TRENDS; HOT AREAS; SEED SELECTION; SURVEY WORKS;

ALGORITHMS;

EID: 84958547679     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-07632-4_19     Document Type: Conference Paper

References (43)

1. Aggarwal, C.C., Reddy, C.K. (eds.) Data Clustering Algorithms and Applications. CRC Press (2014)
2. Arrow, K. Social choice and individual values, 2nd edn. Cowles Foundation, New Haven (1963)
3. Bagrow, J.P., Bollt, E.M. A local method for detecting communities. Phys. Rev. E 72, 046108 (2005)
4. Blondel, V.D., Guillaume, J.I., Lefebvre, E. Fast unfolding of communities in large networks, pp. 1-12 (2008)
5. Bollob́as, B., Riordan, O. Clique percolation. Random Struct. Algorithms 35(3), 294-322 (2009)
6. Chen, J., Zä?ane, O.R., Goebel, R. Local community identification in social networks. In Memon, N., Alhajj, R. (eds.) ASONAM, pp. 237-242. IEEE Computer Society (2009)
7. Chevaleyre, Y., Endriss, U., Lang, J., Maudet, N. A short introduction to computational social choice. In van Leeuwen, J., Italiano, G.F., van der Hoek, W., Meinel, C., Sack, H., Pĺa?sil, F. (eds.) SOFSEM 2007. LNCS, vol. 4362, pp. 51-69. Springer, Heidelberg (2007)
8. Clauset, A. Finding local community structure in networks. Physical Review E (2005)
9. Csardi, G., Nepusz, T. The igraph software package for complex network research. InterJournal Complex Systems 1695 (2006), http://igraph.sf.net
10. Danisch, M., Guillaume, J.-L., Le Grand, B. Unfolding ego-centered community structures with a similarity approach. In Ghoshal, G., Poncela-Casasnovas, J., Tolksdorf, R. (eds.) Complex Networks IV. SCI, vol. 476, pp. 145-153. Springer, Heidelberg (2013)
11. Dwork, C., Kumar, R., Naor, M., Sivakumar, D. Rank aggregation methods for the Web. In WWW, pp. 613-622 (2001)
12. Fortunato, S. Community detection in graphs. Physics Reports 486(3-5), 75-174 (2010)
13. Fred, A.L.N., Jain, A.K. Robust data clustering. In CVPR (2), pp. 128-136. IEEE Computer Society (2003)
14. Giatsidis, C., Malliaros, F.D., Vazirgiannis, M. Advanced graph mining for community evaluation in social networks and the web. In WSDM, pp. 771-772 (2013)
15. Girvan, M., Newman, M.E.J. Community structure in social and biological networks. PNAS 99(12), 7821-7826 (2002)
16. Good, B.H., de Montjoye, Y.A., Clauset, A. The performance of modularity maximization in practical contexts. Physical Review E(81), 046106 (2010)
17. Hubert, L., Arabie, P. Comparing partitions. Journal of Classification 2(1), 192-218 (1985)
18. Kanawati, R. Licod Leaders identification for community detection in complex networks. In SocialCom/PASSAT, pp. 577-582 (2011)
19. Kanawati, R. Empirical evaluation of applying ensemble ranking to ego-centered communities identification in complex networks. In Zaz, Y. (ed.) 4th International Conference on Multimedia Computing and Systems. IEEE, Marrakech (April 2014
20. Kanawati, R. Yasca A collective intelligence approach for community detection in complex networks. CoRR abs/1401.4472 (2014)
21. Khorasgani, R.R., Chen, J., Zaiane, O.R. Top leaders community detection approach in information networks. In 4th SNA-KDD Workshop on Social Network Mining and Analysis, Washington, D.C. (2010)
22. Krebs, V. Political books network, http://www.orgnet.com
23. Labatut, V. Generalized measures for the evaluation of community detection methods. CoRR abs/1303.5441 (2013)
24. Lancichinetti, A., Fortunato, S. Limits of modularity maximization in community detection. CoRR abs/1107.1 (2011)
25. Lee, C., Cunningham, P. Community detection effective evaluation on large social networks. Journal of Complex Networks 2(1), 19-37 (2014)
26. Leskovec, J., Lang, K.J., Dasgupta, A., Mahoney, M.W. Community structure in large networks Natural cluster sizes and the absence of large well-defined clusters. Internet Mathematics 6(1), 29-123 (2009)
27. Lim, K.H., Datta, A. A seed-centric community detection algorithm based on an expanding ring search. In Proceedings of the First Australasian Web Conference, AWC 2013, Adelaide, Australia (2013)
28. Lusseau, D., Schneider, K., Boisseau, O.J., Haase, P., Slooten, E., Dawson, S.M. The bottlenose dolphin community of doubtful sound features a large proportion of long-lasting associations. Behavioral Ecology and Sociobiology 54, 396-405 (2003)
29. Rosvall, M., Axelsson, D., Bergstrom, C.T. The map equation. Eur. Phys. J. Special Topics 13, 178 (2009)
30. Meil?a, M. Comparing clusterings by the variation of information. In Scḧolkopf, B., Warmuth, M.K. (eds.) COLT/Kernel 2003. LNCS (LNAI), vol. 2777, pp. 173-187. Springer, Heidelberg (2003)
31. Palla, G., Deronyi, I., Farkas, I., Vicsek, T. Uncovering the overlapping modular structure of protein interaction networks. FEBS Journal 272, 434 (2005)
32. Papadopoulos, S., Kompatsiaris, Y., Vakali, A. A graph-based clustering scheme for identifying related tags in folksonomies. In Bach Pedersen, T., Mohania, M.K., Tjoa, A.M. (eds.) DaWak 2010. LNCS, vol. 6263, pp. 65-76. Springer, Heidelberg (2010)
33. Papadopoulos, S., Kompatsiaris, Y., Vakali, A., Spyridonos, P. Community detection in social media-performance and application considerations. Data Min. Knowl. Discov. 24(3), 515-554 (2012)
34. Pons, P., Latapy, M. Computing communities in large networks using random walks. J. Graph Algorithms Appl. 10(2), 191-218 (2006)
35. Rand, W.M. Objective criteria for the evaluation of clustering methods. Journal of the American Statistical Association 66, 846-850 (1971)
36. Shah, D., Zaman, T. Community Detection in Networks The Leader-Follower Algorithm. In:Workshop on Networks Across Disciplines in Theory and Applications, NIPS (2010)
37. Strehl, A., Ghosh, J. Cluster ensembles a knowledge reuse framework for combining multiple partitions. The Journal of Machine Learning Research 3, 583-617 (2003)
38. Subbian, K., Melville, P. Supervised rank aggregation for predicting influencers in twitter. In SocialCom/PASSAT, pp. 661-665. IEEE (2011)
39. Tang, L., Liu, H. Community Detection and Mining in Social Media. Synthesis Lectures on Data Mining and Knowledge Discovery. Morgan &Claypool Publishers (2010)
40. Whang, J.J., Gleich, D.F., Dhillon, I.S. Overlapping community detection using seed set expansion. In He, Q., Iyengar, A., Nejdl, W., Pei, J., Rastogi, R. (eds.) CIKM, pp. 2099-2108. ACM (2013)
41. Xie, J., Kelley, S., Szymanski, B.K. Overlapping community detection in networks The state-of-The-art and comparative study. ACM Comput. Surv. 45(4), 43 (2013)
42. Yackoubi, Z., Kanawati, R. Applying leaders driven community detection algorithms to data clustering. In The 36th Annual Conference of the German Classification Society on Data Analysis, Machine Learning and Knowledge Discovery (GfKI 2012) (2012)
43. Zachary, W.W. An information flow model for conflict and fission in small groups. Journal of Anthropological Research 33, 452-473 (1977)