Crowd-based deduplication: An adaptive approach

Proceedings of the ACM SIGMOD International Conference on Management of Data

Volumn 2015-May, Issue , 2015, Pages 1263-1277

  Wang, Sibo ^a   Xiao, Xiaokui ^a   Lee, Chun Hee ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Correlating clustering; Crowdsourcing; Data deduplication

Indexed keywords

CROWDSOURCING;

ADAPTIVE APPROACH; AMAZON MECHANICAL TURKS; BUILDING BLOCKES; CORRELATING CLUSTERING; CORRELATION CLUSTERING; DATA DE DUPLICATIONS; MACHINE-BASED ALGORITHM; STATE-OF-THE-ART TECHNIQUES;

DATA INTEGRATION;

EID: 84957588514     PISSN: 07308078     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2723372.2723739     Document Type: Conference Paper

References (48)

1. http://www.cs.umass.edu/~mccallum/data/cora-refs.tar.gz.
2. http://www.cs.utexas.edu/users/ml/riddle/data/restaurant.tar.gz.
3. http://dbs.uni-leipzig.de/Abt-Buy.zip.
4. https://sourceforge.net/p/acd2015/.
5. N. Ailon, M. Charikar, and A. Newman. Aggregating inconsistent information: ranking and clustering. Journal of the ACM (JACM), 55(5):23, 2008.
6. Y. Amsterdamer, Y. Grossman, T. Milo, and P. Senellart. Crowd mining. In Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data, pages 241-252. ACM, 2013.
7. A. Arasu, M. Götz, and R. Kaushik. On active learning of record matching packages. In Proceedings of the 2010 ACM SIGMOD International Conference on Management of Data, pages 783-794, 2010.
8. A. Arasu, C. Ré, and D. Suciu. Large-scale deduplication with constraints using dedupalog. In Data Engineering, 2009. ICDE'09. IEEE 25th International Conference on, pages 952-963. IEEE, 2009.
9. N. Bansal, A. Blum, and S. Chawla. Correlation clustering. In FOCS, pages 238-, 2002.
10. M. Charikar, V. Guruswami, and A. Wirth. Clustering with qualitative information. In Foundations of Computer Science, 2003. Proceedings. 44th Annual IEEE Symposium on, pages 524-533. IEEE, 2003.
11. Z. Chen, D. V. Kalashnikov, and S. Mehrotra. Exploiting context analysis for combining multiple entity resolution systems. In Proceedings of the 2009 ACM SIGMOD International Conference on Management of data, pages 207-218. ACM, 2009.
12. W. W. Cohen. Integration of heterogeneous databases without common domains using queries based on textual similarity. In ACM SIGMOD Record, volume 27, pages 201-212. ACM, 1998.
13. W. W. Cohen, H. Kautz, and D. McAllester. Hardening soft information sources. In Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, pages 255-259. ACM, 2000.
14. W. W. Cohen and J. Richman. Learning to match and cluster large high-dimensional data sets for data integration. In Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining, pages 475-480. ACM, 2002.
15. S. B. Davidson, S. Khanna, T. Milo, and S. Roy. Using the crowd for top-k and group-by queries. In Proceedings of the 16th International Conference on Database Theory, pages 225-236. ACM, 2013.
16. G. Demartini, D. E. Difallah, and P. Cudré-Mauroux. Zencrowd: leveraging probabilistic reasoning and crowdsourcing techniques for large-scale entity linking. In WWW, pages 469-478, 2012.
17. A. K. Elmagarmid, P. G. Ipeirotis, and V. S. Verykios. Duplicate record detection: A survey. Knowledge and Data Engineering, IEEE Transactions on, 19(1):1-16, 2007.
18. J. Fan, M. Lu, B. C. Ooi, W.-C. Tan, and M. Zhang. A hybrid machine-crowdsourcing system for matching web tables. Technical report, Technical report, National University of Singapore, 2013.
19. A. Feng, M. Franklin, D. Kossmann, T. Kraska, S. Madden, S. Ramesh, A. Wang, and R. Xin. Crowddb: Query processing with the vldb crowd. Proceedings of the VLDB Endowment, 4(12), 2011.
20. M. J. Franklin, D. Kossmann, T. Kraska, S. Ramesh, and R. Xin. Crowddb: answering queries with crowdsourcing. In Proceedings of the 2011 ACM SIGMOD International Conference on Management of data, pages 61-72. ACM, 2011.
21. J. Gemmell, B. I. Rubinstein, and A. K. Chandra. Improving entity resolution with global constraints. arXiv preprint arXiv:1108.6016, 2011.
22. A. Gionis, H. Mannila, and P. Tsaparas. Clustering aggregation. ACM Transactions on Knowledge Discovery from Data (TKDD), 1(1):4, 2007.
23. A. Goder and V. Filkov. Consensus clustering algorithms: Comparison and refinement. In Proceedings of the Tenth Workshop on Algorithm Engineering and Experiments, ALENEX 2008, San Francisco, California, USA, January 19, 2008, 2008.
24. C. Gokhale, S. Das, A. Doan, J. F. Naughton, N. Rampalli, J. W. Shavlik, and X. Zhu. Corleone: hands-off crowdsourcing for entity matching. In Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data, 2014.
25. R. Gomes, P. Welinder, A. Krause, and P. Perona. Crowdclustering. In NIPS, pages 558-566, 2011.
26. S. Guo, A. Parameswaran, and H. Garcia-Molina. So who won?: dynamic max discovery with the crowd. In Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pages 385-396. ACM, 2012.
27. O. Hassanzadeh, F. Chiang, H. C. Lee, and R. J. Miller. Framework for evaluating clustering algorithms in duplicate detection. Proceedings of the VLDB Endowment, 2(1):1282-1293, 2009.
28. M. A. Hernández and S. J. Stolfo. The merge/purge problem for large databases. In ACM SIGMOD Record, volume 24, pages 127-138. ACM, 1995.
29. P. G. Ipeirotis, F. Provost, and J. Wang. Quality management on amazon mechanical turk. In Proceedings of the ACM SIGKDD workshop on human computation, pages 64-67. ACM, 2010.
30. S. R. Jeffery, M. J. Franklin, and A. Y. Halevy. Pay-as-you-go user feedback for dataspace systems. In Proceedings of the 2008 ACM SIGMOD international conference on Management of data, pages 847-860. ACM, 2008.
31. S. R. Jeffery, L. Sun, M. DeLand, N. Pendar, R. Barber, and A. Galdi. Arnold: Declarative crowd-machine data integration. In CIDR, 2013.
32. V. I. Levenshtein. Binary codes capable of correcting deletions, insertions and reversals. In Soviet physics doklady, volume 10, page 707, 1966.
33. X. Liu, M. Lu, B. C. Ooi, Y. Shen, S. Wu, and M. Zhang. Cdas: a crowdsourcing data analytics system. Proceedings of the VLDB Endowment, 5(10):1040-1051, 2012.
34. M. Luby. A simple parallel algorithm for the maximal independent set problem. SIAM journal on computing, 15(4):1036-1053, 1986.
35. A. Marcus, E. Wu, D. Karger, S. Madden, and R. Miller. Human-powered sorts and joins. Proceedings of the VLDB Endowment, 5(1):13-24, 2011.
36. A. McCallum and B. Wellner. Conditional models of identity uncertainty with application to noun coreference. In NIPS, 2004.
37. A. G. Parameswaran, H. Garcia-Molina, H. Park, N. Polyzotis, A. Ramesh, and J. Widom. Crowdscreen: Algorithms for filtering data with humans. In Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pages 361-372. ACM, 2012.
38. A. G. Parameswaran, H. Park, H. Garcia-Molina, N. Polyzotis, and J. Widom. Deco: declarative crowdsourcing. In Proceedings of the 21st ACM international conference on Information and knowledge management, pages 1203-1212. ACM, 2012.
39. L. Philips. Hanging on the metaphone. Computer Language, 7 (12(December)), 1990.
40. E. Rahm and H. H. Do. Data cleaning: Problems and current approaches. IEEE Data Eng. Bull., 23(4):3-13, 2000.
41. W. M. Soon, H. T. Ng, and D. C. Y. Lim. A machine learning approach to coreference resolution of noun phrases. Computational linguistics, 27(4):521-544, 2001.
42. A. Van Zuylen and D. P. Williamson. Deterministic pivoting algorithms for constrained ranking and clustering problems. Mathematics of Operations Research, 34(3):594-620, 2009.
43. P. Venetis and H. Garcia-Molina. Quality control for comparison microtasks. In Proceedings of the First International Workshop on Crowdsourcing and Data Mining, pages 15-21. ACM, 2012.
44. N. Vesdapunt, K. Bellare, and N. Dalvi. Crowdsourcing algorithms for entity resolution. Proceedings of the VLDB Endowment, 7(12), 2014.
45. P. Wais, S. Lingamneni, D. Cook, J. Fennell, B. Goldenberg, D. Lubarov, D. Marin, and H. Simons. Towards building a high-quality workforce with mechanical turk. Proceedings of computational social science and the wisdom of crowds (NIPS), pages 1-5, 2010.
46. J. Wang, T. Kraska, M. J. Franklin, and J. Feng. Crowder: Crowdsourcing entity resolution. Proceedings of the VLDB Endowment, 5(11):1483-1494, 2012.
47. J. Wang, G. Li, T. Kraska, M. J. Franklin, and J. Feng. Leveraging transitive relations for crowdsourced joins. In Proceedings of the 2013 international conference on Management of data, pages 229-240. ACM, 2013.
48. S. E. Whang, P. Lofgren, and H. Garcia-Molina. Question selection for crowd entity resolution. Proceedings of the VLDB Endowment, 6(6):349-360, 2013.