Combining a logical and a numerical method for data reconciliation

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5480 LNCS, Issue , 2009, Pages 66-94

  Saïs, Fatiha ^a   Pernelle, Nathalie ^a   Rousset, Marie Christine ^b  

^a UFR 919 Laboratoire d'Informatique Pour la Mécanique et les Sciences de l'Ingénieur   (France)

^b UNIV GRENOBLE ALPES   (France)

Author keywords

Automatic reasoning; Equation system; Iterative resolution; Ontologies; Reference reconciliation; Semantic Data Integration

Indexed keywords

AUTOMATIC REASONING; EQUATION SYSTEM; ITERATIVE RESOLUTION; REFERENCE RECONCILIATION; SEMANTIC DATA INTEGRATION;

DATA HANDLING; ONTOLOGY;

SEMANTICS;

EID: 68749122161     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-00685-2_3     Document Type: Conference Paper

References (37)

1. Dong, X., Halevy, A., Madhavan, J.: Reference reconciliation in complex information spaces. In: ACM SIGMOD, pp. 85-96. ACM Press, New York (2005)
2. Fellegi, I.P., Sunter, A.B.: A theory for record linkage. Journal of the American Statistical Association 64(328), 1183-1210 (1969)
3. Winkler, W.E.: Overview of record linkage and current research directions. Technical report, Statistical Research Division U.S. Census Bureau Washington, DC 20233 (2006)
4. Verykios, V.S., Elmagarmid, A.K., Houstis, E.N.: Automating the approximate record-matching process. Inf. Sci. Inf. Comput. Sci. 126(1-4), 83-98 (2000)
5. Benjelloun, O., Garcia-Molina, H., Kawai, H., Larson, T.E., Menestrina, D., Su, Q., Thavisomboon, S., Widom, J.: Generic entity resolution in the serf project. IEEE Data Eng. Bull. 29(2), 13-20 (2006)
6. Bhattacharya, I., Getoor, L.: Entity Resolution in Graphs. Wiley, Chichester (2006)
7. Tejada, S., Knoblock, C.A., Minton, S.: Learning object identification rules for information integration. Information Systems 26(8), 607-633 (2001)
8. Rahm, E., Bernstein, P.: A survey of approaches to automatic schema matching. VLDB Journal 10, 334-350 (2001)
9. Shvaiko, P., Euzenat, J.: A survey of schema-based matching approaches. Journal on Data semantics (2005)
10. Galhardas, H., Florescu, D., Shasha, D., Simon, E., Saita, C.: Declarative data cleaning: Language, model and algorithms. In: VLDB 2001 (2001)
11. Bilenko, M., Mooney, R.: Adaptive duplicate detection using learnable string similarity measures. In: SIGKDD 2003 (2003)
12. Ananthakrishna, R., Chaudhuri, S., Ganti, V.: Eliminating fuzzy duplicates in data warehouses. In: ACM SIGMOD. ACM Press, New York (2002)
13. Kalashnikov, D., Mehrotra, S., Chen, Z.: Exploiting relationships for domainindependent data cleaning. In: SIAM Data Mining 2005 (2005)
14. Parag, S., Pedro, D.: Multi-relational record linkage. In: MRDM Workshop (2004)
15. McBride, B.: The Resource Description Framework (RDF) and its Vocabulary Description Language RDFS. In: Handbook on Ontologies, pp. 51-66 (2004)
16. McGuinness, D.L., van Harmelen, F.: OWL Web Ontology Language Overview (February 2004)
17. Horrocks, I., Patel-Schneider, P.F., Boley, H., Tabet, S., Grosof, B., Dean, M.: SWRL: A Semantic Web Rule Language Combining OWL and RuleML (submission) (May 2004)
18. Rodriguez, J.B., Gómez-Pérez, A.: Upgrading relational legacy data to the semantic web. In: WWW 2006: Proceedings of the 15th international conference on World Wide Web, pp. 1069-1070. ACM, New York (2006)
19. Murray, C., Alexander, N., Das, S., Eadon, G., Ravada, S.: Oracle spatial resource description framework (rdf). Technical report, Oracle (2005)
20. Golub, G.H., Van Loan, C.F.: Matrix Computations, 2nd edn., Baltimore, MD, USA (1989)
21. Abiteboul, S., Hull, R., Vianu, V.: Foundations of Databases. Addison-Wesley, Reading (1995)
22. Hayes, P.: RDF Semantics, Technical report (2004), http://www.w3.org/tr/ rdf-mt/
23. Saïs, F., Pernelle, N., Rousset, M.-C.: L2R: A Logical Method for Reference Reconciliation. In: AAAI, pp. 329-334 (2007)
24. Fischer, S.: Two processes of reduplication in the american sign language. Foundations of Language 9, 460-480 (1973)
25. Robinson, A.: A machine-oriented logic based on the resolution principle. Journal ACM 12(1), 23-41 (1965)
26. Chin-Liang, C., Char-Tung Lee, R.: Symbolic Logic and Mechanical Theorem Proving. Academic Press, Inc., London (1997)
27. Henschen, L.J., Wos, L.: Unit refutations and horn sets. J. ACM 21(4), 590-605 (1974)
28. Forbus, K.D., de Kleer, J.: Building problem solvers. MIT Press, Cambridge (1993)
29. Cohen, W.W., Ravikumar, P., Fienberg, S.E.: A comparison of string distance metrics for name-matching tasks. In: IIWeb, pp. 73-78 (2003)
30. Euzenat, J., Valtchev, P.: Similarity-based ontology alignment in owl-lite. In: ECAI, pp. 333-337 (2004)
31. Cohen, W.W., Richman, J.: Learning to match and cluster large high-dimensional data sets for data integration. In: KDD 2002, pp. 475-480. ACM, New York (2002)
32. Newcombe, H.B., Kennedy, J.M., Axford, S.J., James, A.P.: Automatic linkage of vital records. Science 130, 954-959 (1959)
33. Cohen, W.W.: Data integration using similarity joins and a word-based information representation language. ACM Transactions on Information Systems 18(3), 288-321 (2000)
34. Bilke, A., Naumann, F.: Schema matching using duplicates. In: ICDE, pp. 69-80 (2005)
35. Dey, D., Sarkar, S., De, P.: A probabilistic decision model for entity matching in heterogeneous databases. Manage. Sci. 44(10), 1379-1395 (1998)
36. Doan, A., Lu, Y., Lee, Y., Han, J.: Object matching for information integration: A profiler-based approach. In: IIWeb, pp. 53-58 (2003)
37. Adjiman, P., Chatalic, P., Goasdoué, F., Rousset, M.-C., Simon, L.: Distributed reasoning in a peer-to-peer setting: Application to the semantic web. J. Artif. Intell. Res (JAIR) 25, 269-314 (2006)