Consensus clustering based on a new probabilistic rand index with application to subtopic retrieval

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 34, Issue 12, 2012, Pages 2315-2326

  Carpineto, Claudio ^a   Romano, Giovanni ^a  

^a FONDAZIONE UGO BORDONI   (Italy)

Author keywords

Consensus clustering; Probabilistic Rand index; Rand index; Search results clustering; Subtopic retrieval

Indexed keywords

CONSENSUS CLUSTERING; OPTIMIZATION PROBLEMS; PERFORMANCE GAIN; RAND INDEX; SEARCH RESULTS CLUSTERING; STOCHASTIC OPTIMIZATION ALGORITHM; SUBTOPIC RETRIEVAL;

ARTIFICIAL INTELLIGENCE; COMPUTER VISION;

ALGORITHMS;

EID: 84867823027     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2012.80     Document Type: Article

References (43)

1. A.K. Jain, "Data Clustering: 50 Years beyond K-Means," Pattern Recognition Letters, vol. 31, no. 8, pp. 651-666, 2010.
2. A. Fred and A. Jain, "Data Clustering Using Evidence Accumulation," Proc. 16th Int'l Conf. Pattern Recognition, pp. 276-280, 2002. (Pubitemid 44850998)
3. A. Strehl and J. Ghosh, "Cluster Ensembles-A Knowledge Reuse Framework for Combining Multiple Partitions," J. Machine Learning Research, vol. 3, pp. 583-617, 2002.
4. A. Topchy, A.K. Jain, and W. Punch, "A Mixture Model for Clustering Ensembles," Proc. SIAM Int'l Conf. Data Mining, pp. 379-390, 2004.
5. A. Goder and V. Filkov, "Consensus Clustering Algorithms: Comparison and Refinement," Proc. Ninth Workshop Algorithm Eng. and Experiments, pp. 109-117, 2008.
6. X. Wang, C. Yang, and J. Zhou, "Clustering Aggregation by Probability Accumulation," Pattern Recognition, vol. 45, no. 2, pp. 668-675, 2009.
7. S. Vega-Pons, J. Correa-Morris, and J. Ruiz-Shulcloper, "Weighted Partition Consensus via Kernels," Pattern Recognition, vol. 43, no. 8, pp. 2712-2724, 2010.
8. A. Topchy, A.K. Jain, and W. Punc, "Clustering Ensembles: Models of Consensus and Weak Partitions," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 27, no. 12, pp. 1866-1881, Dec. 2005. (Pubitemid 43051385)
9. H. Wang, H. Shan, and A. Banerjee, "Bayesian Cluster Ensembles," Proc. SIAM Int'l Conf. Data Mining, pp. 209-220, 2009.
10. C. Carpineto, S. Osinski, G. Romano, and D. Weiss, "A Survey of Web Clustering Engines," ACM Computing Surveys, vol. 41, no. 3, pp. 1-38, 2009.
11. A. Topchy, A.K. Jain, and W. Punch, "Combining Multiple Weak Clusterings," Proc. IEEE Third Int'l Conf. Data Mining, pp. 331-338, 2003.
12. R. Caruana, M. Elhawary, N. Nguyen, and C. Smith, "Meta Clustering," Proc. Sixth Int'l Conf. Data Mining, pp. 107-118, 2006. (Pubitemid 47485792)
13. W.M. Rand, "Objective Criteria for the Evaluation of Clustering Methods," J. Am. Statistical Assoc., vol. 66, pp. 846-850, 1971.
14. L. Hubert and P. Arabie, "Comparing Partitions," J. Classification, vol. 2, no. 1, pp. 193-218, 1985.
15. N.X. Vinh, J. Epps, and J. Bailey, "Information Theoretic Measures for Clustering Comparison: Is a Correction for Chance Necessary?" Proc. 26th Ann. Int'l Conf. Machine Learning, pp. 1073-1080, 2009.
16. R.J.G.B. Campello, "A Fuzzy Extension of the Rand Index and Other Related Indexes for Clustering and Classification Assessment," Pattern Recognition Letters, vol. 28, no. 7, pp. 833-841, 2007. (Pubitemid 46290586)
17. A. Ben-Hur, A. Elisseeff, and I. Guyon, "A Stability Based Method for Discovering Structure in Clustered Data," Proc. Pacific Symp. Biocomputing, pp. 6-17, 2002.
18. J. Barthélemy and B. Leclerc, "The Median Procedure for Partitions," Partitioning Data Sets, I.J. Cox, P. Hansen, and B. Julesz, eds., pp. 3-34, Am. Math. Soc., 1995.
19. Y. Wakabayashi, "The Complexity of Computing Medians of Relations," Resenhas, vol. 3, no. 3, pp. 323-349, 1998.
20. V. Filkov and S. Skiena, "Integrating Microarray Data by Consensus Clustering," Proc. IEEE 15th Int'l Conf. Tools with Artificial Intelligence, pp. 418-426, 2003.
21. A. Gionis, H. Mannila, and P. Tsaparas, "Clustering Aggregation," ACM Trans. Knowledge Discovery from Data, vol. 1, no. 4, 2007.
22. T. Li and C. Ding, "Weighted Consensus Clustering," Proc. SIAM Int'l Conf. Data Mining, pp. 789-8092, 2008.
23. R. Unnikrishnan and M. Hebert, "Measures of Similarity," Proc. IEEE Seventh Workshop Applications of Computer Vision, pp. 394-400, 2005. (Pubitemid 47592201)
24. M. Mela, "Comparing Clusterings: An Axiomatic View," Proc. 22nd Int'l Conf. Machine Learning, pp. 577-584, 2005.
25. P. Wang, C. Domeniconi, and K.B. Laskey, "Nonparametric Bayesian Clustering Ensembles," Proc. European Conf. Machine Learning and Knowledge Discovery in Databases, pp. 435-450, 2010.
26. R. Bekkerman, M. Scholz, and K. Viswanatah, "Improving Clustering Stability with Combinatorial MRFs," Proc. 15th ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining, pp. 99-108, 2009.
27. X.Z. Fern and W. Lin, "Cluster Ensemble Selection," Statistical Analysis and Data Mining, vol. 1, no. 3, pp. 128-141, 2008.
28. J. Azimi and X. Fern, "Adaptive Cluster Ensemble Selection," Proc. 21st Int'l Jont Conf. Artifical Intelligence, pp. 992-997, 2009.
29. N. Bansal, A. Blum, and S. Chawla, "Correlation Clustering," Proc. IEEE 43rd Ann. Symp. Foundations of Computer Science, pp. 238-250, 2002.
30. P. Bonizzoni, G.D. Vedova, R. Dondi, and T. Jiang, "On the Approximation of Correlation Clustering and Consensus Clustering," J. Computer and System Sciences, vol. 74, no. 5, pp. 671-696, 2008. (Pubitemid 351685699)
31. C. Carpineto and G. Romano, "Optimal Meta Search Results Clustering," Proc. 33rd Int'l ACM SIGIR Conf. Research and Development in Information Retrieval, pp. 170-177, 2010.
32. G.L. Liu, Introduction to Combinatorial Mathematics. McGraw Hill, 1968.
33. D. Cristofor and D. Simovici, "Finding Median Partitions Using Information-Theoretical-Based Genetic Algorithms," J. Universal Computer Science, vol. 8, no. 2, pp. 153-172, 2002.
34. F. Leisch, "Bagged Clustering," Adaptive Information Systems and Modelling in Economics and Management Science, technical report Working Papers SFB WU Vienna Univ. of Economics and Business, vol. 51, 1999.
35. E. Dimitriadou, A. Weingessel, and F. Hornik, "A Combination Scheme for Fuzzy Clustering," Int'l J. Pattern Recognition and Artificial Intelligence, vol. 16, no. 7, pp. 901-912, 2002.
36. S. Osinski and D. Weiss, "A Concept-Driven Algorithm for Clustering Search Results," IEEE Intelligent Systems, vol. 20, no. 3, pp. 48-54, May 2005. (Pubitemid 40860490)
37. A. Bernardini, C. Carpineto, and M. D'Amico, "Full-Subtopic Retrieval with Keyphrase-Based Search Results Clustering," Proc. IEEE/WIC/ACM Int'l Joint Conf. Web Intelligence and Intelligent Agent Technology, pp. 206-213, 2009.
38. U. Manber and G. Myers, "Suffix Arrays: A New Method for On- Line String Searches," SIAM J. Computing, vol. 22, no. 5, pp. 935-948, 1993.
39. S. Deerwester, S.T. Dumais, G.W. Furnas, T.K. Landauer, and T.K. Harshman, "Indexing by Latent Semanic Analysis," J. Am. Soc. for Information Science, vol. 41, no. 6, pp. 391-407, 1990.
40. E. Ukkonen, "On-Line Construction of Suffix Trees," Algorithmica, vol. 14, no. 3, pp. 249-260, 1995.
41. C. Carpineto, S. Mizzaro, G. Romano, and M. Snidero, "Mobile Information Retrieval with Search Results Clustering: Prototypes and Evaluations," J. Am. Soc. for Information Science and Technology, vol. 60, no. 5, pp. 877-895, 2009.
42. K. van Rijsbergen, Information Retrieval. Butterworth-Heinemann, 1979.
43. C.D. Manning, P. Raghavan, and H. Schütze, Introduction to Information Retrieval. Cambridge Univ. Press, 2008.