Clustering large probabilistic graphs

IEEE Transactions on Knowledge and Data Engineering

Volumn 25, Issue 2, 2013, Pages 325-336

  Kollios, George ^a   Potamias, Michalis ^b   Terzi, Evimaria ^a  

^a BOSTON UNIVERSITY   (United States)

^b GROUPON INC   (United States)

Author keywords

clustering algorithms; probabilistic databases; probabilistic graphs; Uncertain data

Indexed keywords

CLUSTERINGS; CORRELATION CLUSTERING; GRAPH CLUSTERING; NUMBER OF CLUSTERS; OBJECTIVE FUNCTIONS; PROBABILISTIC DATABASE; PROBABILISTIC GRAPHS; PROTEIN-PROTEIN INTERACTION NETWORKS; SOCIAL NETWORKS; STATISTICAL SIGNIFICANCE; UNCERTAIN DATAS;

APPROXIMATION ALGORITHMS; GRAPHIC METHODS; PROTEINS;

CLUSTERING ALGORITHMS;

EID: 84871822063     PISSN: 10414347     EISSN: None     Source Type: Journal    
DOI: 10.1109/TKDE.2011.243     Document Type: Article

References (47)

1. H. Frank, "Shortest Paths in Probabilistic Graphs," Operations Research, vol. 17, no. 4, pp. 583-599, 1969.
2. L. G. Valiant, "The Complexity of Enumeration and Reliability Problems," SIAM J. Computing, vol. 8, no. 3, pp. 410-421, 1979.
3. N. J. Krogan et al., "Global Landscape of Protein Complexes in the Yeast Saccharomyces Cerevisiae," Nature, vol. 440, no. 7084, pp. 637-643, http://dx. doi. org/10. 1038/nature04670, Mar. 2006.
4. S. E. Schaeffer, "Graph Clustering," Computer Science Rev., vol. 1, no. 1, pp. 27-64, 2007.
5. O. Benjelloun, A. D. Sarma, A. Halevy, and J. Widom, "ULDBs: Databases with Uncertainty and Lineage," Proc. 32nd Int'l Conf. Very Large Data Bases (VLDB), pp. 953-964, 2006
6. N. N. Dalvi and D. Suciu, "Efficient Query Evaluation on Probabilistic Databases," Proc. 13th Int'l Conf. Very Large Data Bases (VLDB), 2004.
7. M. Potamias, F. Bonchi, A. Gionis, and G. Kollios, "K-Nearest Neighbors in Uncertain Graphs," Proc. VLDB Endowment, vol. 3, nos. 1/2, pp. 997-1008, 2010.
8. Z. Zou, H. Gao, and J. Li, "Discovering Frequent Subgraphs over Uncertain Graph Databases under Probabilistic Semantics," Proc. 16th ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining (KDD), pp. 633-642, 2010.
9. R. Shamir, R. Sharan, and D. Tsur, "Cluster Graph Modification Problems," Discrete Applied Math., vol. 144, nos. 1/2, pp. 173-182, 2004.
10. N. Bansal, A. Blum, and S. Chawla, "Correlation Clustering," Machine Learning, vol. 56, nos. 1-3, pp. 89-113, 2004.
11. U. Brandes, M. Gaertler, and D. Wagner, "Engineering Graph Clustering: Models and Experimental Evaluation," ACM J. Experimental Algorithmics, vol. 12, article 1. 1, pp. 1-26, 2007.
12. G. Karypis and V. Kumar, "Parallel Multilevel K-Way Partitioning for Irregular Graphs," SIAM Rev., vol. 41, pp. 278-300, 1999.
13. M. Newman, "Modularity and Community Structure in Networks," Proc. Nat'l Academy of Sciences USA, vol. 103, pp. 8577-8582, 2006. (Pubitemid 43878062)
14. Y. Emek, A. Korman, and Y. Shavitt, "Approximating the Statistics of Various Properties in Randomly Weighted Graphs," Proc. 22nd Ann. ACM-SIAM Symp. Discrete Algorithms (SODA), pp. 1455-1467. 2011
15. P. Hintsanen and H. Toivonen, "Finding Reliable Subgraphs from Large Probabilistic Graphs," Data Mining Knowledge Discovery, vol. 17, no. 1, pp. 3-23, 2008.
16. X. Lian and L. Chen, "Efficient Query Answering in Probabilistic Rdf Graphs," Proc. ACM SIGMOD Int'l Conf. Management of Data (SIGMOD '11), pp. 157-168, 2011.
17. O. Papapetrou, E. Ioannou, and D. Skoutas, "Efficient Discovery of Frequent Subgraph Patterns in Uncertain Graph Databases," Proc. 14th Int'l Conf. Extending Database Technology (EDBT), pp. 355-366, 2011.
18. Z. Zou, J. Li, H. Gao, and S. Zhang, "Frequent Subgraph Pattern Mining on Uncertain Graph Data," Proc. 18th ACM Conf. Information and Knowledge Management (CIKM), pp. 583-592, 2009.
19. M. Hua and J. Pei, "Probabilistic Path Queries in Road Networks: Traffic Uncertainty Aware Path Selection," Proc. 13th Int'l Conf. Extending Database Technology (EDBT), pp. 347-358, 2010.
20. Y. Yuan, L. Chen, and G. Wang, "Efficiently Answering Probability Threshold-Based Shortest Path Queries over Uncertain Graphs," Proc. 15th Int'l Conf. Database Systems for Advanced Applications (DASFAA), pp. 155-170, 2010.
21. C. C. Aggarwal and P. S. Yu, "A Framework for Clustering Uncertain Data Streams," Proc. IEEE 24th Int'l Conf. Data Eng. (ICDE), pp. 150-159, 2008.
22. G. Cormode and A. McGregor, "Approximation Algorithms for Clustering Uncertain Data," Proc. 27th ACM SIGMOD-SIGACTSIGART Symp. Principles of Database Systems (PODS), pp. 191-200, 2008.
23. S. Günnemann, H. Kremer, and T. Seidl, "Subspace Clustering for Uncertain Data," Proc. SIAM Int'l Conf. Data Mining (SDM), pp. 385-396, 2010.
24. S. Guha and K. Munagala, "Exceeding Expectations and Clustering Uncertain Data," Proc. 28th ACM SIGMOD-SIGACT-SIGART Symp. Principles of Database Systems (PODS), pp. 269-278, 2009.
25. B. Kao, S. D. Lee, F. K. F. Lee, D. W.-L. Cheung, and W.-S. Ho, "Clustering Uncertain Data Using Voronoi Diagrams and R-Tree Index," IEEE Trans. Knowledge Data Eng., vol. 22, no. 9, pp. 1219-1233, Sept. 2010.
26. H.-P. Kriegel and M. Pfeifle, "Density-Based Clustering of Uncertain Data," Proc. 11th ACM SIGKDD Int'l Conf. Knowledge Discovery in Data Mining (KDD), pp. 672-677, 2005. (Pubitemid 43218338)
27. W. K. Ngai, B. Kao, C. K. Chui, R. Cheng, M. Chau, and K. Y. Yip, "Efficient Clustering of Uncertain Data," Proc. Sixth Int'l Conf. Data Mining (ICDM), pp. 436-445, 2006. (Pubitemid 47485823)
28. T. Bernecker, H.-P. Kriegel, M. Renz, F. Verhein, and A. Zuefle, "Probabilistic Frequent Itemset Mining in Uncertain Databases," Proc. 15th ACM SIGKDD Int'l Conf. Knowledge Discovery in Data Mining (KDD), 2009.
29. L. Sun, R. Cheng, D. W. Cheung, and J. Cheng, "Mining Uncertain Data with Probabilistic Guarantees," Proc. 16th ACM SIGKDD Int'l Conf. Knowledge Discovery in Data Mining (KDD), pp. 273-282, 2010.
30. Q. Zhang, F. Li, and K. Yi, "Finding Frequent Items in Probabilistic Data," Proc. ACM SIGMOD Int'l Conf. Management of Data (SIGMOD), pp. 819-832, 2008.
31. M. L. Yiu, N. Mamoulis, X. Dai, Y. Tao, and M. Vaitis, "Efficient Evaluation of Probabilistic Advanced Spatial Queries on Existentially Uncertain Data," IEEE Trans. Knowledge and Data Eng., vol. 21, no. 1, pp. 108-122, Jan. 2009.
32. N. N. Dalvi, C. Ré, and D. Suciu, "Probabilistic Databases: Diamonds in the Dirt," Comm. ACM, vol. 52, no. 7, pp. 86-94, 2009.
33. C. Koch, "Approximating Predicates and Expressive Queries on Probabilistic Databases," Proc. 27th ACM SIGMOD-SIGACTSIGART Symp. Principles of Database Systems (PODS), 2008.
34. C. Re, N. N. Dalvi, and D. Suciu, "Efficient Top-K Query Evaluation on Probabilistic Data," Proc. IEEE 23rd Int'l Conf. Data Eng. (ICDE), 2007.
35. G. Cormode, F. Li, and K. Yi, "Semantics of Ranking Queries for Probabilistic Data and Expected Ranks," Proc. IEEE Int'l Conf. Data Eng. (ICDE), 2009.
36. M. Hua, J. Pei, W. Zhang, and X. Lin, "Ranking Queries on Uncertain Data: A Probabilistic Threshold Approach," Proc. ACM SIGMOD Int'l Conf. Management of Data (SIGMOD), 2008.
37. J. Li, B. Saha, and A. Deshpande, "A Unified Approach to Ranking in Probabilistic Databases," Proc. VLDB Endowment, vol. 2, no. 1, pp. 502-513, 2009.
38. M. Soliman, I. Ilyas, and K. C.-C. Chang, "Top-k Query Processing in Uncertain Databases," Proc. IEEE 23rd Int'l Conf. Data Eng. (ICDE), 2007.
39. K. Yi, F. Li, G. Kollios, and D. Srivastava, "Efficient Processing of Top-k Queries in Uncertain Databases with X-Relations," IEEE Trans. Knowledge Data Eng., vol. 20, no. 12, pp. 1669-1682, Dec. 2008.
40. B. Bollobs, Random Graphs. Cambridge Univ. Press, 2001.
41. R. Motwani and P. Raghavan, Randomized Algorithms. Cambridge Univ. Press, 2000.
42. N. Ailon, M. Charikar, and A. Newman, "Aggregating Inconsistent Information: Ranking and Clustering," Proc. Annual ACM Symp. Theory of Computing (STOC), pp. 684-693, 2005. (Pubitemid 43098641)
43. A. Gionis, H. Mannila, and P. Tsaparas, "Clustering Aggregation," ACM Trans. Knowledge Discovery from Data (TKDD), vol. 1, no. 1, article 4, pp. 1-30, 2007.
44. A. Ben-Dor, R. Shamir, and Z. Yakhini, "Clustering Gene Expression Patterns," J. Computational Biology, vol. 6, no. 3/4, pp. 281-297, 1999.
45. H. Mewes et al. "Mips: Analysis and Annotation of Proteins from Whole Genomes," Nucleic Acids Research, vol. 32, pp. D41-D44, 2004. (Pubitemid 38081600)
46. S. Lattanzi and D. Sivakumar, "Affiliation Networks," Proc. 41st Annual ACM Symp. Theory of Computing (STOC), pp. 427-434, 2009.
47. A. L. Barabási and R. Albert, "Emergence of Scaling in Random Networks," Science, vol. 286, no. 5439, pp. 509-512, 1999.