Toward finding hidden communities based on user profile

Proceedings - IEEE International Conference on Data Mining, ICDM

Volumn , Issue , 2010, Pages 380-387

  Yoshida, Tetsuya ^a  

^a HOKKAIDO UNIVERSITY   (Japan)

Author keywords

Community detection; Eigenvector; Embedding; Modularity; Profile

Indexed keywords

COMMUNITY DETECTION; EIGENVECTOR; EMBEDDING; MODULARITY; PROFILE;

DATA MINING; EIGENVALUES AND EIGENFUNCTIONS; POPULATION DYNAMICS;

ARTS COMPUTING;

EID: 79951760670     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDMW.2010.20     Document Type: Conference Paper

References (16)

1. S. Basu, I. Davidson, and K. Wagstaff, editors. Constrained Clustering: Advances in Algorithms, Theory, and Applications. Chapman & Hall/CRC Press, 2008.
2. M. Belkin and P. Niyogi. Laplacian eigenmaps for dimensionality reduction and data representation. Neural Computation, 15:1373-1396, 2002.
3. O. Chapelle, B. Schölkopf, and A. Zien, editors. Semi- Supervised Learning. MIT Press, 2006.
4. F. Chung. Spectral Graph Theory. American Mathematical Society, 1997.
5. T. Cover and J. Thomas. Elements of Information Theory. Wiley, 2006.
6. Duncan J. Watts. Six Degrees: The Science of a Connected Age. W W Norton & Co Inc, 2004.
7. J. Kleinberg. Authoritative sources in a hyperlinked environment. Journal of the ACM, 46(5):604-632, 1999.
8. M. Newman. Finding community structure using the eigenvectors of matrices. Physical Review E, 76(3):036104, 2006.
9. Peter Mika. Social Networks and the Semantic Web. Springer, 2007.
10. P. Pons and M. Latapy. Computing communities in large networks using random walks. Journal of Graph Algorithms, 10(2):191-218, 2006.
11. U. Raghavan, R. Albert, and S. Kumara. Near linear time algorithm to detect community structures in large-scale networks. Physical Review E, 76:036106, 2007.
12. E. Ristad. A Natural Law of Succession. Technical Report CS-TR-495-95, Princeton University, 1995.
13. J. Shawe-Taylor and N. Cristianini. Kernel Methods for Pattern Analysis. Cambridge University Press, 2004.
14. U. von Luxburg. A tutorial on spectral clustering. Statistics and Computing, 17(4):395-416, 2007.
15. T. Yoshida. A graph model for mutual information based clustering. Journal of Intelligent Information Systems, 2010. accepted.
16. T. Yoshida. Performance Evaluation of Constraints in Graph-based Semi-Supervised Clustering. In Proc. AMT-2010 (LNAI 6335 ), pages 138-149, 2010.