Is there a best quality metric for graph clusters?

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

Volumn 6911 LNAI, Issue PART 1, 2011, Pages 44-59

  Almeida, Hélio ^a   Guedes, Dorgival ^a   Meira Jr , Wagner ^a   Zaki, Mohammed J ^b  

^a FEDERAL UNIVERSITY OF MINAS GERAIS   (Brazil)

^b RENSSELAER POLYTECHNIC INSTITUTE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTER STRUCTURE; GRAPH CLUSTERING; LARGER NETWORKS; QUALITY EVALUATION; QUALITY METRICES; QUALITY METRICS; REAL-WORLD GRAPHS; CLUSTER QUALITIES; GRAPH CLUSTERING ALGORITHMS;

LEARNING SYSTEMS; QUALITY CONTROL; DATA MINING; GRAPH ALGORITHMS; MACHINE LEARNING; PETROLEUM RESERVOIR EVALUATION;

CLUSTERING ALGORITHMS;

EID: 80052398024     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-23780-5_13     Document Type: Conference Paper

References (24)

1. Brandes, U., Gaertler, M., Wagner, D.: Engineering graph clustering: Models and experimental evaluation. J. Exp. Algorithmics 12, 1-26 (2008)
2. Danon, L., Díaz-Guilera, A., Duch, J., Arenas, A.: Comparing community structure identification. Journal of Statistical Mechanics: Theory and Experiment 2005(09), P09008 (2005)
3. Dhillon, I.S., Guan, Y., Kulis, B.: Weighted graph cuts without eigenvectors a multilevel approach. IEEE Trans. Pattern Anal. Mach. Intell. 29(11), 1944-1957 (2007)
4. Van Dongen, S.: Graph clustering via a discrete uncoupling process. SIAM Journal on Matrix Analysis and Applications 30(1), 121-141 (2008)
5. Girvan, M., Newman, M.E.J.: Community structure in social and biological networks. Proceedings of the National Academy of Sciences of the United States of America 99(12), 7821-7826 (2002)
6. Good, B.H., de Montjoye, Y.A., Clauset, A.: Performance of modularity maximization in practical contexts. Physical Review E 81(4), 046106+ (2010)
7. Gustafson, M., Lombardi, A.: Comparison and validation of community structures in complex networks. Physica A: Statistical Mechanics and its Application 367, 559-576 (2006)
8. Kannan, R., Vempala, S., Vetta, A.: On clusterings: Good, bad and spectral. J. ACM 51(3), 497-515 (2004)
9. Kumar, R., Raghavan, P., Rajagopalan, S., Tomkins, A.: Trawling the web for emerging cyber-communities. Comput. Netw. 31, 1481-1493 (1999)
10. Leskovec, J., Lang, K.J., Dasgupta, A., Mahoney, M.W.: Statistical properties of community structure in large social and information networks. In: WWW 2008: Proceeding of the 17th International Conference on World Wide Web, pp. 695-704. ACM, New York (2008)
11. Leskovec, J., Lang, K.J., Mahoney, M.: Empirical comparison of algorithms for network community detection. In: Proceedings of the 19th International Conference on World Wide Web, WWW 2010, pp. 631-640. ACM, New York (2010)
12. Nepusz, T., Bazso, F.: Likelihood-based clustering of directed graphs, pp. 189-194 (March 2007)
13. Nepusz, T., Sasidharan, R., Paccanaro, A.: Scps: a fast implementation of a spectral method for detecting protein families on a genome-wide scale. BMC Bioinformatics 11(1), 120 (2010)
14. Newman, M.E., Girvan, M.: Finding and evaluating community structure in networks. Physical Review E 69(2) (February 2004)
15. Newman, M.E.J.: Mixing patterns in networks. Phys. Rev. E 67(2), 26126 (2003)
16. Newman, M.E.J., Girvan, M.: Mixing Patterns and Community Structure in Networks. In: Pastor-Satorras, R., Rubi, M., Diaz-Guilera, A. (eds.) Statistical Mechanics of Complex Networks. Lecture Notes in Physics, vol. 625, pp. 66-87. Springer, Berlin (2003)
17. Schaeffer, S.E.: Graph clustering. Computer Science Review 1(1), 27-64 (2007)
18. Shi, J., Malik, J.: Normalized cuts and image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 22, 888-905 (2000)
19. Steinbach, M., Karypis, G., Kumar, V.: A comparison of document clustering techniques. In: Grobelnik, M., Mladenic, D., Milic-Frayling, N. (eds.) KDD-2000 Workshop on Text Mining, Boston, MA, August 20, pp. 109-111 (2000)
20. Tan, P.-N., Kumar, V., Srivastava, J.: Selecting the right interestingness measure for association patterns. In: KDD 2002: Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 32-41. ACM, New York (2002)
21. Tan, P.-N., Steinbach, M., Kumar, V.: Introduction to Data Mining. Addison- Wesley Longman Publishing Co., Inc., Boston (2005)
22. van Dongen, S.M.: Graph Clustering by Flow Simulation. PhD thesis, University of Utrecht, The Netherlands (2000)
23. Zachary, W.W.: An information flow model for conflict and fission in small groups. Journal of Anthropological Research 33, 452-473 (1977)
24. Zhou, Y., Cheng, H., Yu, J.X.: Graph clustering based on structural/attribute similarities. Proc. VLDB Endow. 2(1), 718-729 (2009)