Overlapping correlation clustering

Knowledge and Information Systems

Volumn 35, Issue 1, 2013, Pages 1-32

  Bonchi, Francesco ^a   Gionis, Aristides ^a   Ukkonen, Antti ^a  

^a YAHOO RESEARCH   (Spain)

Author keywords

Algorithms; Clustering; Correlation clustering; Overlapping clustering; Pregel

Indexed keywords

ALGORITHMS; ITERATIVE METHODS; OPTIMIZATION;

CLUSTERING; CORRELATION CLUSTERING; ITERATIVE LOCAL SEARCH METHOD; JACCARD COEFFICIENTS; OPTIMIZATION PROBLEMS; OVERLAPPING CLUSTERING; OVERLAPPING CLUSTERS; PREGEL;

CLUSTERING ALGORITHMS;

EID: 84875417842     PISSN: 02191377     EISSN: 02193116     Source Type: Journal    
DOI: 10.1007/s10115-012-0522-9     Document Type: Article

References (59)

1. Ailon N, Charikar M, Newman A (2005) Aggregating inconsistent information: ranking and clustering. In: Proceedings of the ACM symposium on theory of computing (STOC).
2. Ailon N, Liberty E (2009) Correlation clustering revisited: the "true" cost of error minimization problems. In: Automata, languages and programming, 36th international colloquium (ICALP).
3. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ (1990) Basic local alignment search tool. J Mol Biol 215(3): 403-410.
4. Arabie P, Carroll JD, DeSarbo W, Wind J (1981) Overlapping clustering: a new method for product positioning. J Mark Res 18(3): 310-317.
5. Banerjee A, Krumpelman C, Ghosh J, Basu S, Mooney RJ (2005) Model-based overlapping clustering. In: Proceedings of the 11th ACM SIGKDD international conference on knowledge discovery and data mining (KDD).
6. Bansal N, Blum A, Chawla S (2004) Correlation clustering. Mach Learn 56(1-3): 89-113.
7. Basu S, Banerjee A, Mooney RJ (2004) Active semi-supervision for pairwise constrained clustering. In: Proceedings of the Fourth SIAM international conference on data mining (SDM).
8. Basu S, Bilenko M, Mooney RJ (2004) A probabilistic framework for semi-supervised clustering. In: Proceedings of the tenth ACM SIGKDD international conference on knowledge discovery and data mining (KDD).
9. Battle A, Segal E, Koller D (2004) Probabilistic discovery of overlapping cellular processes and their regulation. In: Proceedings of the 8th international conference on research in computational molecular biology (RECOMB).
10. Bezdek, JC, Pal, SK (eds) (1992) Fuzzy models for pattern recognition-methods that search for structures in data. IEEE Press, New York.
11. Brin S, Page L (1998) The anatomy of a large-scale hypertextual web search engine. Comput Netw 30(1-7): 107-117.
12. Broder AZ, Charikar M, Frieze AM, Mitzenmacher M (1998) Min-wise independent permutations. In: Proceedings of the 13th annual ACM symposium on theory of computing (STOC).
13. Charikar M, Guruswami V, Wirth A (2003) Clustering with qualitative information. In: Proceedings of the IEEE symposium on foundations of computer science (FOCS).
14. Chen L, Özsu MT, Oria V (2005) Robust and fast similarity search for moving object trajectories. In: Proceedings of the 2005 ACM SIGMOD international conference on management of data (SIGMOD'05).
15. Cheng Y, Church GM (2000) Biclustering of expression data. In: Proceedings of the eighth international conference on intelligent systems for molecular biology (ISMB).
16. Chierichetti F, Kumar R, Pandey S, Vassilvitskii S (2010) Finding the jaccard median. In: Proceedings of the 21st annual ACM-SIAM symposium on discrete algorithms (SODA).
17. Coe PK, Johnson BK, Stewart KM, Kie JG (2004) Spatial and temporal interactions of elk, mule deer, and cattle. In: Transactions of the 69th North American wildlife and natural resources conference, pp 656-669.
18. Davidson I, Ravi SS (2005) Clustering with constraints: feasibility issues and the k-means algorithm. In: Proceedings of the Fifth SIAM international conference on data mining (SDM).
19. Davidson I, Ravi SS (2007) Intractability and clustering with constraints. In: Proceedings of the 24th international conference on machine learning (ICML).
20. Dean J, Ghemawat S (2008) Mapreduce: simplified data processing on large clusters. Commun ACM 51(1): 107-113.
21. Demaine ED, Emanuel D, Fiat A, Immorlica N (2006) Correlation clustering in general weighted graphs. Theor Comput Sci 361: 172-187.
22. Ding C, He X, Simon HD (2005) On the equivalence of nonnegative matrix factorization and spectral clustering. In: Proceedings of the SIAM data mining conference.
23. Fortunato S (2010) Community detection in graphs. Phys Rep 486: 75-174.
24. Fu Q, Banerjee A (2008) Multiplicative mixture models for overlapping clustering. In: Proceedings of the 8th IEEE international conference on data mining (ICDM).
25. Fu Q, Banerjee A (2009) Bayesian overlapping subspace clustering. In: Proceedings of the 9th IEEE international conference on data mining (ICDM).
26. Gaffney S, Smyth P (1999) Trajectory clustering with mixtures of regression models. In: Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining, KDD '99.
27. Garey MR, Johnson DS (1979) Computers and intractability: a guide to the theory of NP-completeness. W. H. Freeman & Co., San Francisco.
28. Gionis A, Mannila H, Tsaparas P (2007) Clustering aggregation. TKDD 1(1): Article 4.
29. Giotis I, Guruswami V (2006) Correlation clustering with a fixed number of clusters. In: Proceedings of the seventeenth annual ACM-SIAM symposium on discrete algorithms (SODA).
30. Hasan M, Salem S, Zaki M (2011) Simclus: an effective algorithm for clustering with a lower bound on similarity. Knowl Inf Syst 28: 665-685.
31. Hathaway RJ, Davenport JW, Bezdek JC (1989) Relational duals of the c-means clustering algorithms. Pattern Recognit 22(2): 205-212.
32. Hathaway RJ, Hu Y (2009) Density-weighted fuzzy c-means clustering. IEEE T Fuzzy Syst 17(1): 243-252.
33. He Z, Xie S, Zdunek R, Zhou G, Cichocki A (2011) Symmetric nonnegative matrix factorization: algorithms and applications to probabilistic clustering. IEEE Trans Neural Netw 22(12): 2117-2131.
34. Indyk P, Motwani R (1998) Approximate nearest neighbors: towards removing the curse of dimensionality. In: Proceedings of the 13th annual ACM symposium on theory of computing (STOC).
35. Klein D, Kamvar SD, Manning CD (2002) From instance-level constraints to space-level constraints: making the most of prior knowledge in data clustering. In: Proceedings of the nineteenth international conference on machine learning (ICML).
36. Kobayashi M, Aono M (2006) Exploring overlapping clusters using dynamic re-scaling and sampling. Knowl Inf Syst 10: 295-313.
37. Lee DD, Seung HS (2001) Algorithms for Non-negative Matrix Factorization. In: Advances in neural information processing systems 13: 556-562.
38. Lee JG, Han J, Whang KY (2007) Trajectory clustering: a partition-and-group framework. In: Proceedings of the 2007 ACM SIGMOD international conference on management of data, SIGMOD '07.
39. Madeira SC, Oliveira AL (2004) Biclustering algorithms for biological data analysis: a survey. IEEE/ACM Trans Comput Biol Bioinform 1(1): 24-45.
40. Malewicz G, Austern MH, Bik AJC, Dehnert JC, Horn I, Leiser N, Czajkowski G (2010) Pregel: a system for large-scale graph processing. In: SIGMOD conference, pp 135-146.
41. Mei JP, Chen L (2010) Fuzzy clustering with weighted medoids for relational data. Pattern Recognit 43(5): 1964-1974.
42. Miettinen P (2008) On the positive-negative partial set cover problem. Inf Process Lett 108(4): 219-221.
43. Murzin A, Brenner S, Hubbard T, Chothia C (1995) Scop-a structural classification of proteins database for the investigation of sequences and structures. J Mol Biol 247(4): 536-540.
44. Nanni M, Pedreschi D (2006) Time-focused clustering of trajectories of moving objects. J Intell Inf Syst 27(3): 267-289.
45. Nepusz T, Sasidharan R, Paccanaro A (2010) Scps: a fast implementation of a spectral method for detecting protein families on a genome-wide scale. BMC Bioinform 11(1): 120.
46. Paccanaro A, Casbon JA, Saqi MAS (2006) Spectral clustering of protein sequences. Nucleic Acids Res 34(5): 1571-1580.
47. Palla G, Derenyi I, Farkas I, Vicsek T (2005) Uncovering the overlapping community structure of complex networks in nature and society. Nature.
48. Scheinerman ER, Tucker K (2010) Modeling graphs using dot product representations. Comput Stat 25(1): 1-16.
49. Scripps J, Tan PN (2006) Clustering in the presence of bridge-nodes. In: Proceedings of the sixth SIAM international conference on data mining (SDM).
50. Segal E, Battle A, Koller D (2003) Decomposing gene expression into cellular processes. In: Proceedings of the 8th Pacific symposium on biocomputing (PSB).
51. Shafiei MM, Milios EE (2006) Model-based overlapping co-clustering. In: Proceedings of the fourth workshop on text mining.
52. Shepard RN, Arabie P (1979) Additive clustering: representation of similarities as combinations of discrete overlapping properties. Psychol Rev 86(2): 87-123.
53. Swamy C (2004) Correlation clustering: maximizing agreements via semidefinite programming. In: Proceedings of the ACM-SIAM symposium on discrete algorithms (SODA).
54. Tang L, Liu H (2009) Scalable learning of collective behavior based on sparse social dimensions. In: Proceedings of the 18th ACM conference on information and knowledge management (CIKM).
55. Valiant LG (1990) A bridging model for parallel computation. Commun ACM 33(8): 103-111.
56. Wagstaff K, Cardie C (2000) Clustering with instance-level constraints. In: Proceedings of the 17th international conference on machine learning (ICML).
57. Wagstaff K, Cardie C, Rogers S, Schrödl S (2001) Constrained k-means clustering with background knowledge. In: Proceedings of the 18th international conference on machine learning (ICML).
58. Wang X, Tang L, Gao H, Liu H (2010) Discovering overlapping groups in social media. In: The 10th IEEE international conference on data mining (ICDM).
59. Xiong H, Steinbach M, Ruslim A, Kumar V (2009) Characterizing pattern preserving clustering. Knowl Inf Syst 19: 311-336.