Swoosh: a generic approach to entity resolution

Ananthakrishna, R., Chaudhuri, S., Ganti, V.: Eliminating fuzzy duplicates in data warehouses. In: Proceedings of VLDB, pp. 586–597 (2002)

Arasu, A., Ganti, V., Kaushik, R.: Efficient exact set-similarity joins. In: VLDB, pp. 918–929 (2006)

Bansal, N., Blum, A., Chawla, S.: Correlation clustering. In: FOCS, p. 238 (2002)

Baxter, R., Christen, P., Churches, T.: A comparison of fast blocking methods for record linkage. In: Proceedings of ACM SIGKDD’03 Workshop on Data Cleaning, Record Linkage, and Object Consolidation (2003). http://citeseer.ist.psu.edu/article/baxter03comparison.html

Bekkerman, R., McCallum, A.: Disambiguating web appearances of people in a social network. In: WWW, pp. 463–470 (2005)

Benjelloun, O., Garcia-Molina, H., Jonas, J., Menestrina, D., Whang, S., Su, Q., Widom, J.: Swoosh : a generic approach to entity resolution. Technical Report, Stanford University (2006). http://dbpubs.stanford.edu/pub/2005-5

Benjelloun, O., Garcia-Molina, H., Kawai, H., Larson, T.E., Menestrina, D., Thavisomboon, S.: D-Swoosh : a family of algorithms for generic, distributed entity resolution. In: ICDCS (2007)

Bhattacharya, I., Getoor, L.: Iterative record linkage for cleaning and integration. In: Proceedings of SIGMOD Workshop on Research Issues on Data Mining and Knowledge Discovery (2004)

Bhattacharya, I., Getoor, L.: A latent dirichlet model for unsupervised entity resolution. In: Sixth SIAM Conference on Data Mining (2006)

Blume, M.: Automatic entity disambiguation: benefits to NER, relation extraction, link analysis, and inference. In: International Conference on Intelligence Analysis (2005). https://analysis.mitre.org/

Chaudhuri, S., Ganjam, K., Ganti, V., Motwani, R.: Robust and efficient fuzzy match for online data cleaning. In: Proceedings of ACM SIGMOD, pp. 313–324 (2003)

Chaudhuri, S., Ganti, V., Motwani, R.: Robust identification of fuzzy duplicates. In: Proceedings of ICDE, Tokyo, Japan (2005)

Cohen, W.: Data integration using similarity joins and a word-based information representation language. ACM Trans. Inf. Syst. 18, 288–321 (2000)

Dong, X., Halevy, A.Y., Madhavan, J.: Reference reconciliation in complex information spaces. In: Proceedings of ACM SIGMOD (2005)

Fellegi, I.P., Sunter, A.B.: A theory for record linkage. J. Am. Stat. Assoc. 64(328), 1183–1210 (1969)

Galhardas, H., Florescu, D., Shasha, D., Simon, E., Saita, C.A.: Declarative data cleaning: Language, model, and algorithms. In: Proceedings of VLDB, pp. 371–380 (2001)

Gravano, L., Ipeirotis, P.G., Jagadish, H.V., Koudas, N., Muthukrishnan, S., Srivastava, D.: Approximate string joins in a database (almost) for free. In: VLDB, pp. 491–500 (2001)

Gu, L., Baxter, R., Vickers, D., Rainsford, C.: Record linkage: current practice and future directions. Technical Report 03/83, CSIRO Mathematical and Information Sciences (2003)

Hernández, M.A., Stolfo, S.J.: The merge/purge problem for large databases. In: Proceedings of ACM SIGMOD, pp. 127–138 (1995)

Hernández, M.A., Stolfo, S.J.: Real-world data is dirty: data cleansing and the merge/purge problem. Data Min. Knowl. Discov. 2(1), 9–37 (1998)

IBM: DB2 Entity Analytic Solutions. http://www-306.ibm.com/software/data/db2/eas/

Jaro, M.A.: Advances in record-linkage methodology as applied to matching the 1985 census of tampa, florida. J. Am. Stat. Assoc. 84(406), 414–420 (1989)

Jin, L., Li, C., Mehrotra, S.: Efficient record linkage in large data sets. In: Proceedings of International Conference on Database Systems for Advanced Applications, p. 137 (2003)

Kalashnikov, D.V., Mehrotra, S., Chen, Z.: Exploiting relationships for domain-independent data cleaning. In: Proceedings of the SIAM International Conference on Data Mining, Newport Beach, CA (2005)

McCallum, A.K., Nigam, K., Ungar, L.: Efficient clustering of high-dimensional data sets with application to reference matching. In: Proceedings of KDD, pp. 169–178, Boston, MA (2000)

Menestrina, D., Benjelloun, O., Garcia-Molina, H.: Generic entity resolution with data confidences. In: CleanDB (2006)

Monge, A.E., Elkan, C.: An efficient domain-independent algorithm for detecting approximately duplicate database records. In: Proceedings of SIGMOD Workshop on Research Issues on Data Mining and Knowledge Discovery, pp. 23–29 (1997)

Motro, A., Anokhin, P.: Fusionplex: resolution of data inconsistencies in the integration of heterogeneous information sources. Inf. Fusion 7(2), 176–196 (2006)

Newcombe, H.B., Kennedy, J.M., Axford, S.J., James, A.P.: Automatic linkage of vital records. Science 130(3381), 954–959 (1959)

Parag, D.P.: Multi-relational record linkage. In: Proceedings of the KDD-2004 Workshop on Multi-Relational Data Mining, pp. 31–48 (2004)

Sarawagi, S., Bhamidipaty, A.: Interactive deduplication using active learning. In: Proceedings of ACM SIGKDD, Edmonton, Alberta (2002)

Schallehn, E., Sattler, K.U., Saake, G.: Extensible and similarity-based grouping for data integratio. In: ICDE, p. 277 (2002)

Singla, P., Domingos, P.: Object identification with attribute-mediated dependences. In: Proceedings of PKDD, pp. 297 – 308 (2005)

Smith, T.F., Waterman, M.S.: Identification of common molecular subsequences. J. Mol. Biol. 147, 195–197 (1981)

Tarjan, R.E.: Efficiency of a good but not linear set union algorithm. J. ACM. 22(2), 215–225 (1975)

Tejada, S., Knoblock, C.A., Minton, S.: Learning object identification rules for information integration. Inf. Syst. J. 26(8), 635–656 (2001)

Verykios, V.S., Moustakides, G.V., Elfeky, M.G.: A bayesian decision model for cost optimal record matching. VLDB J. 12(1), 28–40(2003). http://www.cs.purdue.edu/homes/mgelfeky/Papers/vldbj12(1 ).pdf

Winkler, W.: Overview of record linkage and current research directions. Technical Report, Statistical Research Division, U.S. Bureau of the Census, Washington, DC (2006)

Winkler, W.E.: Using the EM algorithm for weight computation in the Fellegi–Sunter model of record linkage. In: American Statistical Association, Proceedings of the Section on Survey Research Methods, pp. 667–671 (1988)