ClusterJoin: A similarity joins framework using Map-reduce

Proceedings of the VLDB Endowment

Volumn 7, Issue 12, 2014, Pages 1059-1070

  Sarma, Akash Das ^a   He, Yeye ^b   Chaudhuri, Surajit ^b  

^a STANFORD UNIVERSITY   (United States)

^b MICROSOFT RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA DISTRIBUTION; DISTANCE FUNCTIONS; DYNAMIC LOAD BALANCING SCHEMES; EXPERIMENTAL EVALUATION; HIGH DIMENSIONAL DATA; METRIC DISTANCES; PROBABILISTIC GUARANTEES; SIMILARITY SCORES;

CLUSTERING ALGORITHMS;

EID: 84905106551     PISSN: None     EISSN: 21508097     Source Type: Conference Proceeding    
DOI: 10.14778/2732977.2732981     Document Type: Conference Paper

References (27)

1. Linkedgeodata: http://linkedgeodata.org.
2. Openstreetmap: www.openstreetmap.org.
3. F. Afrati, A. Das Sarma, A. Rajaraman, P. Rule, S. Salihoglu, and J. Ullman. Anchor points algorithms for hamming and edit distance. In Proceedings of ICDT, 2014.
4. F. N. Afrati, A. D. Sarma, D. Menestrina, A. G. Parameswaran, and J. D. Ullman. Fuzzy joins using mapreduce. In Proceedings of ICDE, 2012.
5. A. Arasu, V. Ganti, and R. Kaushik. Efficient exact set-similarity joins. In Proceedings of VLDB, 2006.
6. R. J. Bayardo, Y. Ma, and R. Srikant. Scaling up all pairs similarity search. In Proceedings of WWW, 2007.
7. K. S. Beyer, J. Goldstein, R. Ramakrishnan, and U. Shaft. When is "nearest neighbor" meaningful? In Proceedings of ICDT, 1999.
8. A. Z. Broder, S. C. Glassman, M. S. Manasse, and G. Zweig. Syntactic clustering of the web. In Computer Networks, 1997.
9. V. Bryant. Metric Spaces: Iteration and Application. Cambridge University Press, 1985.
10. R. Chaiken, B. Jenkins, P. Larson, and B. Ramsey. Scope: Easy and efficient parallel processing of massive data sets. In Proceedings of VLDB, 2008.
11. S. Chaudhuri, V. Ganti, and R. Kaushik. A primitive operator for similarity joins in data cleaning. In Proceedings of ICDE, 2006.
12. J. Dean and S. Ghemawat. Mapreduce: Simplified data processing on large clusters. In Communication of ACM, 2010.
13. D. Deng, G. Li, S. Hao, J. Wang, and J. Feng. Massjoin: A mapreduce-based algorithm for string similarity joins. In Proceedings of ICDE, 2013.
14. A. Doan, A. Halevy, and Z. Ives. Principles of data integration. In Morgan Kaufmann, 2012.
15. D. M. Endres and J. E. Schindelin. A new metric for probability distributions. In IEEE Trans. Inf. Theory, 2003.
16. M. R. Henzinger. Finding near-duplicate web pages: a large-scale evaluation of algorithms. In Proceedings of SIGIR, 2006.
17. T. C. Hoad and J. Zobel. Methods for identifying versioned and plagiarized documents. In JASIST 54(3), 2003.
18. A. Metwally and C. Faloutsos. V-smart-join: A scalable mapreduce framework for all-pair similarity joins of multisets and vectors. In Proceedings of VLDB, 2012.
19. D. A. Nehme-Haily. The set-union knapsack problem. University of Texas at Austin, Thesis, 1995.
20. A. Okabe, B. Boots, K. Sugihara, and S. N. Chiu. Spatial tessellations: Concepts and applications of voronoi diagrams. 2009.
21. A. Okcan and M. Riedewald. Processing theta-joins using mapreduce. In Proceedings of SIGMOD, 2011.
22. V. Satuluri and S. Parthasarathy. Bayesian locality sensitive hashing for fast similarity search. In Proceedings of VLDB, 2012.
23. Y. N. Silva and J. M. Reed. Exploiting mapreduce-based similarity joins. In Proceedings of SIGMOD, 2012.
24. R. Vernica, M. J. Carey, and C. Li. Efficient parallel set-similarity joins using mapreduce. In Proceedings of SIGMOD, 2010.
25. Y. Wang, A. Metwally, and S. Parthasarathy. Scalable all-pairs similarity search in metric spaces. In Proceedings of KDD, 2013.
26. W. Winkler. The state of record linkage and current research problems. In Technical Report, US Bureau of Census, 1999.
27. C. Xiao, W. Wang, X. Lin, and J. X. Yu. Efficient similarity joins for near duplicate detection. In Proceedings of WWW, 2008.