A flexible system for ontology matching

Lecture Notes in Business Information Processing

Volumn 107 LNBIP, Issue , 2012, Pages 79-94

  Ngo, DuyHoa ^a   Bellahsene, Zohra ^a   Coletta, Remi ^a  

^a INRIA   (France)

Author keywords

cost sensitive classification; flexibility; machine learning; Ontology matching; self configuration

Indexed keywords

INFORMATION SYSTEMS; LEARNING SYSTEMS;

BENCHMARK DATASETS; COST-SENSITIVE CLASSIFICATION; FLEXIBILITY; FLEXIBLE SYSTEM; ONTOLOGY MATCHING; PRECISION AND RECALL; SELF CONFIGURATION;

BENCHMARKING;

EID: 84861136156     PISSN: 18651348     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-29749-6_6     Document Type: Conference Paper

References (22)

1. Chawla, N.V., Cieslak, D.A., Hall, L.O., Joshi, A.: Automatically countering imbalance and its empirical relationship to cost. Data Min. Knowl. Discov. 17(2), 225-252 (2008)
2. Doan, A., Madhavan, J., Domingos, P., Halevy, A.Y.: Ontology matching: A machine learning approach. In: Handbook on Ontologies, pp. 385-404 (2004)
3. Domingos, P.: Metacost: A general method for making classifiers cost-sensitive. In: Knowledge Discovery and Data Mining, pp. 155-164. ACM Press (1999)
4. Drummond, C., Holte, R.C.: Cost curves: an improved method for visualizing classifier performance. In: Machine Learning, pp. 95-130 (2006)
5. Duchateau, F., Coletta, R., Bellahsene, Z., Miller, R.J.: Yam: a schema matcher factory. In: CIKM Conference, pp. 2079-2080 (2009)
6. Eckert, K., Meilicke, C., Stuckenschmidt, H.: Improving Ontology Matching Using Meta-level Learning. In: Aroyo, L., Traverso, P., Ciravegna, F., Cimiano, P., Heath, T., Hyvönen, E., Mizoguchi, R., Oren, E., Sabou, M., Simperl, E. (eds.) ESWC 2009. LNCS, vol. 5554, pp. 158-172. Springer, Heidelberg (2009)
7. Elkan, C.: The foundations of cost-sensitive learning. In: Artificial Intelligence, pp. 973-978 (2001)
8. Euzenat, J., Shvaiko, P.: Ontology matching. Springer, Heidelberg (2007)
9. Dillon, T.S., Chang, E., Meersman, R., Sycara, K.: Advances in Ontology Matching. In: Dillon, T.S., Chang, E., Meersman, R., Sycara, K. (eds.) Advances in Web Semantics I. LNCS, vol. 4891, pp. 1-6. Springer, Heidelberg (2008)
10. Gruber, T.R.: A translation approach to portable ontology specifications. Knowledge Acquisition 5, 199-220 (1993)
11. Hall, M.A.: Correlation-based feature selection for discrete and numeric class machine learning. In: ICML, pp. 359-366 (2000)
12. Ichise, R.: Machine learning approach for ontology mapping using multiple concept similarity measures. In: ICIS Conference, pp. 340-346. IEEE Computer Society, Washington, DC (2008)
13. Kalfoglou, Y., Marco Schorlemmer, W.: Ontology mapping: The state of the art. In: Semantic Interoperability and Integration (2005)
14. Lin, F., Sandkuhl, K.: A Survey of Exploiting Wordnet in Ontology Matching. In: Bramer, M. (ed.) Artificial Intelligence and Practice II. IFIP AICT, vol. 276, pp. 341-350. Springer, Heidelberg (2008)
15. Mao, M., Peng, Y., Spring, M.: Ontology mapping: As a binary classification problem. In: Semantics, Knowledge and Grid Conference, pp. 20-25 (2008)
16. Ngo, D., Bellasene, Z., Coletta, R.: A generic approach for combining linguistic and context profile metrics in ontology matching. In: ODBASE Conference (2011)
17. Maio, N.S.P., Bettencourt, N., Rocha, J.: Evaluating a confidence value for ontology alignment. In: Ontology Matching Workshop (OM 2007) (November 2007)
18. Rahm, E., Bernstein, P.A.: A survey of approaches to automatic schema matching. VLDB J. 10(4), 334-350 (2001)
19. Shvaiko, P., Euzenat, J.: Ten Challenges for Ontology Matching. In: Meersman, R., Tari, Z. (eds.) OTM 2008, Part II. LNCS, vol. 5332, pp. 1164-1182. Springer, Heidelberg (2008)
20. Stoilos, G., Stamou, G., Kollias, S.: A String Metric for Ontology Alignment. In: Gil, Y., Motta, E., Benjamins, V.R., Musen, M.A. (eds.) ISWC 2005. LNCS, vol. 3729, pp. 624-637. Springer, Heidelberg (2005)
21. Svátek, V.: Combining ontology mapping methods using bayesian networks. In: ISWC Workshop (2006)
22. Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. Morgan Kaufmann (October 1999)