Joint Cluster Analysis of Attribute Data and Relationship Data: The Connected k-Center Problem, Algorithms and Applications

ACM Transactions on Knowledge Discovery from Data

Volumn 2, Issue 2, 2008, Pages 1-35

  Ge, Rong ^a   Ester, Martin ^a   Gao, Byron J ^a   Hu, Zengjian ^a   Bhattacharya, Binay ^a   Ben Moshe, Boaz ^b  

^a SIMON FRASER UNIVERSITY   (Canada)

^b ARIEL UNIVERSITY   (Israel)

Author keywords

Algorithms; Management; Performance

Indexed keywords

EID: 84859109801     PISSN: 15564681     EISSN: 1556472X     Source Type: Journal    
DOI: 10.1145/1376815.1376816     Document Type: Article

References (57)

1. Agarwal, P. and Procopiuc, C. M. 2002. Exact and approximation algorithms for clustering. Algorithmica 33, 2, 201-226.
2. ANKERST, M., BREUNIG, M. M., KRIEGEL, H., and SANDER, J. 1999. Optics: Ordering points to identify the clustering structure. In Proceedings of the ACM SIGMOD International Conference on Management of Data (Philadelphia, PA). ACM, New York, 49-60
3. Barabasi, A. L., Jeong, H., Neda, Z., Ravasz, E., Schubert, A., and Vicseks, T. 2002. Evolution of the social network of scientific collaborations. Physica A 311, 3-4, 590-614
4. Bartal, Y., Charikar, M., Andraz,D. 2001. Approximating min-sum-clustering in metric spaces. In Proceedings on 33rd Annual ACM Symposium on Theory of Computing (Hersonissos, Greece). ACM, New York, 11-20
5. Basu, S., Bilenko, M., and Mooney, R. J. 2004. A probabilistic framework for semi-supervised clustering. In Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (Seattle, WA). ACM, New York, 5968
6. Berriz, G. F., King, O. D., Bryant, B., Sander, C., and Roth, F. P. 2003. Characterizing gene sets with funcassociate. Bioinformatics 19, 18, 2502-2504
7. Brandes, U., Gaertler, M., and Wagner, D. 2003. Experiments on graph clustering algorithms. In Proceedings of the 11th Annual European Symposium on Algorithms (Budapest, Hungary). Springer-Verlag, Berlin/Heidelberg, Germany, 568-579
8. Brucker, P. 1977. On the complexity of clustering problems. In Optimization and Operations Research, R. Hehn, B. Korte, and W. Oettli, Eds. Springer-Verlag, Berlin, Germany, 45-54
9. Chan, P. K., Schlag, M. D. F., and Zien, J. Y. 1994. Spectral k-way ratio-cut partitioning and clustering. IEEE Trans. Computer-Aided Desi. Integ. Circ. Syst. 13, 9, 1088-1096
10. Charikar, M., Guha, S., Tardos, E., and Shmoys, D. 1999. A constant factor approximation algorithm for the k-median problem. J. Comput. Syst. Sci. 65, 1, 129-149
11. Charikar, M. and Panigrahy, R. 2004. Clustering to minimize the sum of cluster diameters. J. Comput. Syst. Sci. 68, 2, 417-441
12. Citeseer. 2006. Scientific literature digital library
13. Davidson, I. and Ravi, S. S. 2005. Clustering with constraints: Feasibility issues and the k-means algorithm. In Proceedings of the 5th SIAM International Conference on Data Mining (Newport Beach, CA). Society for Industrial and Applied Mathematics, Philadelphia, PA, 138-149
14. Dhillon, I. S., Guan, Y., and Kulis, B. 2007. Weighted graph cuts without eigenvectors: A multilevel approach. IEEE Transactions on Pattern Analysis and Machine Intelligence 29, 11, 1944-1957
15. Doddi, S., Marathe, M. V., Ravi, S. S., Taylor, D., and Widmayer, P. 2000. Approximation algorithms for clustering to minimize the sum of diameters. In Proceedings of the 7th Scandinavian Workshop on Algorithm Theory (Bergen, Norway). Springer-Verlag, Berlin/Heidelberg, Germany, 237-250
16. Dyer, M. and Frieze, A. M. 1985. A simple heuristic for the p-center problem. Oper. Res. Lett. 3, 285-288
17. Ester, M., Ge, R., Gao, B. J., Hu, Z., and Ben-Moshe, B. 2006. Joint cluster analysis of attribute data and relationship data: the connected k-center problem. In Proceedings of the 6th SIAM Conference on Data Mining (Bethesda, MD). Society for Industrial and Applied Mathematics, Philadelphia, PA, 246-257
18. Ester, M., Kriegel, H., Sander, J., and Xu, X. 1996. A density-based algorithm for discovering clusters in large spatial databases with noise. In Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining (Portland, OR). AAAI Press, 226-231
19. Feder, T. and Greene, D. H. 1988. Optimal algorithms for approximate clustering. In Proceedings of the 20th Annual ACM Symposium on Theory of Computing (Chicago, IL). ACM, New York, 434-444
20. Frederickson, G. N. and Johnson, D. B. 1979. Optimal algorithms for generating quantile information in x + y and matrices with sorted columns. In Proceedings of the 13th Annual Conference on Information Science and Systems. The Johns Hopkins Univ., Baltimore, MD, 47-52
21. Gonzalez, T. 1985. Clustering to minimize the maximum inter-cluster distance. Theoret. Comput. Sci. 38, 2-3, 293-306
22. Guha, S., Rastogi, R., and Shim, K. 1999. Rock: A robust clustering algorithm for categorical attributes. In Proceedings of the 15th International Conference on Data Engineering (Sydney, Austrialia). IEEE Computer Society, Los Alamitos, CA, 512-521
23. Guttman-Beck, N. and Hassin, R. 1998. Approximation algorithms for min-sum p-clustering. Disc. Appl. Math. 89, 1-3, 125-142
24. Hanisch, D., Zien, A., Zimmer, R., and Lengauer, T. 2002. Co-clustering of biological networks and gene expression data. Bioinformatics 18, S145-S154
25. Hanneman, R. A. and Riddle, M. 2005. Introduction to social network methods
26. Hartuv, E. and Shamir, R. 2000. A clustering algorithm based on graph connectivity. Inf. Proc. Lett. 76, 4-6, 175-181
27. Hochbaum, D. and Shmoys, D. 1985. A best possible heuristic for the k-center problem. Math. Oper. Res. 10, 180-184
28. Iacobucci, D. 1996. Networks in Marketing. Sage Publications, Thousand Oaks, CA
29. Jain, A. and Dubes, R. 1988. Algorithms for clustering data. Prentice-Hall, Englewood Cliffs, NJ
30. Jain, K. and Vazirani, V. 2001. Approximation algorithms for metric facility location and k-median problems using the primal-dual scheme and lagrangian relaxation. J. ACM 48, 2, 274-296
31. Kariv, O. and Hakimi, S. L. 1979. An algorithmic approach to network location problems, Part II: p-medians. SIAM J. Appl. Math. 37, 539-560
32. Karypis, G., Han, E., and Kumar, V. 1999. Chameleon: Hierarchical clustering using dynamic modeling. IEEE Comput. 32, 8, 68-75
33. Kaufman, L. and Rousseeuw, P. 1990. Finding Groups in Data: An Introduction to Cluster Analysis. Wiley, New York
34. Kulis, B., Basu, S., Dhillon, I. S., and Mooney, R. 2005. Semi-supervised graph clustering: A kernel approach. In Proceedings of the 22nd International Conference on Machine Learning (Bonn, Germany). ACM, New York, 457-464
35. Lin, J. and Vitter, J. 1992. Approximation algorithms for geometric median problems. Inf. Proc. Lett. 44, 5, 245-249
36. Lloyd, S. 1982. Least squares quantization in pcm. IEEE Trans. Inf. Theory 28, 2, 129-136
37. Macqueen, J. 1967. Some methods for classification and analysis of multivariate observations. In Proceedings of the 5th Berkeley Symposium on Mathematics, Statistics and Probability. 281-297
38. Megiddo, N. and Supowit, K. J. 1984. On the complexity of some common geometric location problems. SIAM Journal on Computing 13, 1, 182-196
39. Megiddo, N., Tamir, A., Zemel, E., and Chandrasekaran, R. 1981. An o(n log2 n) algorithm for the k-th longest path in a tree with applications to location problems. SIAM J. Comput. 10, 2, 328-337
40. Moser, F., Ge, R., and Ester, M. 2007. Joint cluster analysis of attribute and relationship data without a-priori specification of the number of clusters. In Proceedings of the 13 th ACM SIGKDD
41. International Conference On Knowledge Discovery and Data Mining (San Jose, Ca). Acm, New York
42. Ng, R. T. and Han, J. 1994. Efficient and effective clustering methods for spatial data mining. In Proceedings of the 20th International Conference on Very Large Data Bases (Santiago de Chile, Chile). Morgan Kaufmann, San Francisco, CA, 144-155
43. Scott, J. 2000. Social Network Analysis: A handbook. Sage Publications, Thousand Oaks, CA
44. Segal, E., Wang, H., and Koller, D. 2003. Discovering molecular pathways from protein interaction and gene expression data. Bioinformatics (Suppl. 1) 19, 264-272
45. Shi, J. and Malik, J. 2000. Normalized cuts and image segmentation. IEEE Trans. Patt. Analysis and Machine Intelligence 22, 8, 888-905
46. Spellman, P. T., Sherlock, G., Zhang, M. Q., Iyer, V. R., Anders, K., Eisen, M. B., Brown, P. O., Botstein, D., and Futcher, B. 1998. Comprehensive identification of cell cycle-regulated genes of the yeast saccharomyces cerevisiae by microarray hybridization. Molec. Biol. Cell 9, 12, 3273-3297
47. Stark, C., Breitkreutz, B., Reguly, T., Boucher, L., Breitkreutz, A., and Tyers, M. 2006. Biogrid: A general repository for interaction datasets. Nucleic Acids Res. 34, D535-D539
48. Steinbach, M., Karypis, G., and Kumar, V. 2000. A comparison of document clustering techniques. in KDD Workshop on Text Mining
49. Steinhaus, H. 1956. Sur la division des corp materiels en parties. Bulletin LAcadmie Polonaise des Science C1. III, IV, 801-804
50. Swamy, C., and Kumar, A. 2004. Primal-dual algorithms for connected facility location problems. Algorithmica 40, 4, 245-269
51. Tamir, A. 1996. An o(pn2) algorithm for the p-median and related problems on tree graphs. Operations Research Letters 19, 59-64
52. Taskar, B., Segal, E., and Koller, D. 2001. Probabilistic classification and clustering in relational data. In Proceedings of 17th International Joint Conference on Artificial Intelligence (Seattle, WA). Morgan Kaufmann, San Francisco, CA, 870-878
53. Toregas, C., Swan, R., Revelle, C., and Bergman, L. 1971. The location of emergency service facilities. Oper. Res. 19, 1363-1373
54. Tung, A. K. H., Ng, R. T., Lakshmanan, L. V. S., and Han, J. 2001. Constraint-based clustering in large databases. In Proceedings of the 8th International Conference on Database Theory (London, UK). Springer-Verlag, New York, 405-419
55. Ulitsky, I. and Shamir, R. 2007. Identification of functional modules using network topology and high-throughput data. BMC System Biology 1, 8
56. Wasserman, S. and Faust, K. 1994. Social Network Analysis. Cambridge University Press, Cambridge, UK
57. Webster, C. and Morrison, P. 2004. Network analysis in marketing. Australasian Market. J. 12, 2, 8-18