A clustering-based framework to control block sizes for entity resolution

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn 2015-August, Issue , 2015, Pages 279-288

  Fisher, Jeffrey ^a   Christen, Peter ^a   Wang, Qing ^a   Rahm, Erhard ^b  

^a AUSTRALIAN NATIONAL UNIVERSITY   (Australia)

^b UNIVERSITY OF LEIPZIG   (Germany)

Author keywords

Blocking; Data cleaning; Indexing; Record linkage

Indexed keywords

CLUSTERING ALGORITHMS; DATA HANDLING; DATA MINING; DATA PRIVACY; ECONOMIC AND SOCIAL EFFECTS; INDEXING (OF INFORMATION); VIRTUAL REALITY;

BLOCKING; CLUSTERING-BASED FRAMEWORK; DATA CLEANING; HIERARCHICAL CLUSTERING APPROACH; PAIR-WISE COMPARISON; PRIVACY PRESERVING RECORD LINKAGES; REAL-WORLD ENTITIES; RECORD LINKAGE;

QUALITY CONTROL;

EID: 84954139187     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2783258.2783396     Document Type: Conference Paper

References (25)

1. I. Bhattacharya and L. Getoor. Collective entity resolution in relational data. ACM TKDD, 1(1), 2007.
2. P. Christen. Data matching: concepts and techniques for record linkage, entity resolution, and duplicate detection. Springer, 2012.
3. P. Christen. A survey of indexing techniques for scalable record linkage and deduplication. IEEE TKDE, 24(9), 2012.
4. P. Christen. Preparation of a real temporal voter data set for record linkage and duplicate detection research. Technical report, Australian National University, 2014.
5. A. Das Sarma, A. Jain, A. Machanavajjhala, and P. Bohannon. An automatic blocking mechanism for large-scale de-duplication tasks. In ACM CIKM, pages 1055-1064, 2012.
6. X. Dong, A. Halevy, and J. Madhavan. Reference reconciliation in complex information spaces. In ACM SIGMOD, pages 85-96, 2005.
7. A. K. Elmagarmid, P. G. Ipeirotis, and V. S. Verykios. Duplicate record detection: A survey. IEEE TKDE, 19(1):1-16, 2007.
8. I. P. Fellegi and A. B. Sunter. A theory for record linkage. JASA, 64(328):1183-1210, 1969.
9. Z. Fu, P. Christen, and J. Zhou. A graph matching method for historical census household linkage. In PAKDD, Springer LNAI Vol. 8443, pages 485-496. 2014.
10. N. Ganganath, C.-T. Cheng, and C. Tse. Data clustering with cluster size constraints using a modified k-means algorithm. In CyberC, pages 158-161, Oct 2014.
11. M. A. Hernandez and S. J. Stolfo. Real-world data is dirty: Data cleansing and the merge/purge problem. Springer DMKD, 2(1):9-37, 1998.
12. D. Kalashnikov and S. Mehrotra. Domain-independent data cleaning via analysis of entity-relationship graph. ACM TODS, 31(2):716-767, 2006.
13. M. Kejriwal and D. P. Miranker. An unsupervised algorithm for learning blocking schemes. In IEEE ICDM, pages 340-349, 2013.
14. H. Kim and D. Lee. Parallel linkage. In ACM CIKM, pages 283-292, 2007.
15. H. Köpcke and E. Rahm. Frameworks for entity matching: A comparison. Elsevier DKE, 69(2):197-210, 2010.
16. M. Malinen and P. Fränti. Balanced k-means for clustering. In SSSPR, Springer LNCS Vol. 8621, pages 32-41. 2014.
17. B. Ramadan and P. Christen. Unsupervised blocking key selection for real-time entity resolution. In PAKDD, Springer LNAI Vol. 9078, pages 574-585, 2015.
18. B. Ramadan, P. Christen, and H. Liang. Dynamic sorted neighborhood indexing for real-time entity resolution. In ADC, Springer LNCS Vol. 8506, pages 1-12. 2014.
19. D. Rebollo-Monedero, M. Solé, J. Nin, and J. Forné. A modification of the k-means method for quasi-unsupervised learning. Elsevier KBS, 37(0):176-185, 2013.
20. P. Singla and P. Domingos. Entity resolution with Markov logic. In IEEE ICDM, pages 572-582, 2006.
21. D. Vatsalan and P. Christen. Sorted nearest neighborhood clustering for efficient private blocking. In PAKDD, Volume 7819 of LNCS, pages 341-352. Springer, 2013.
22. D. Vatsalan, P. Christen, and V. S. Verykios. A taxonomy of privacy-preserving record linkage techniques. Elsevier IS, 38(6):946-969, 2013.
23. S. E. Whang, D. Menestrina, G. Koutrika, M. Theobald, and H. Garcia-Molina. Entity resolution with iterative blocking. In ACM SIGMOD, pages 219-232, 2009.
24. R. Xu and I. Wunsch, D. Survey of clustering algorithms. IEEE TNN, 16(3):645-678, May 2005.
25. S. Zhu, D. Wang, and T. Li. Data clustering with size constraints. Elsevier KBS, 23(8):883-889, 2010.