Integration of ontology data through learning instance matching

Proceedings - 2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2006 Main Conference Proceedings), WI'06

Volumn , Issue , 2006, Pages 536-539

  Wang, Chao ^a   Lu, Jie ^a   Zhang, Guangquan ^a  

^a UNIVERSITY OF TECHNOLOGY SYDNEY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

DATA REDUCTION; LEARNING SYSTEMS; WEB SERVICES;

MATCHING METHOD; ONTOLOGY DATA;

ONTOLOGY;

EID: 42549155168     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WI.2006.100     Document Type: Conference Paper

References (14)

1. F. Baader, D. Calvanese, D. McGuinness, D. Nardi, and P. Patel-Schneider, editors. The description logic handbook: theory, implementation, and applications. Cambridge University Press, New York, 2002.
2. R. Baeza-Yates and B. d. A. N. Ribeiro. Modern information retrieval. Addison-Wesley Longman, 1999.
3. M. Bilenko and R. J. Mooney. Adaptive duplicate detection using learnable string similarity measures. In KDD '03, pages 39-48, New York, NY, USA, 2003. ACM Press.
4. W. W. Cohen and J. Richman. Learning to match and cluster large high-dimensional data sets for data integration. In KDD '02, pages 475-480, 2002.
5. A. Doan and A. Y. Halevy. Semantic-integration research in the database community. AIMag., 26(1):83-94, 2005.
6. A. Doan, Y. Lu, Y. Lee, and J. Han. Profile-based object matching for information integration. IEEE Intelligent Systems, 18(5):54-59, 2003.
7. A. Doan, J. Madhavan, P. Domingos, and A. Halevy. Learning to map between ontologies on the semantic web. In WWW '02, pages 662-673. 2002.
8. D. Gusfield. Algorithms on strings, trees, and sequences: computer science and computational biology. Cambridge University Press, 1997.
9. A. McCallum, K. Nigam, and L. H. Ungar. Efficient clustering of high-dimensional data sets with application to reference matching. In KDD '00, pages 169-178, New York, NY, USA, 2000. ACM Press.
10. D. L. McGuinness and F. v. Harmelen. Owl web ontology language overview. w3c recommendation. http://www.w3.org/tr/owl-features/, 2004.
11. G. Salton and C. Buckley. Term-weighting approaches in automatic text retrieval. Inf. Process. Manage., 24(5):513-523, 1988.
12. S. Tejada, C. A. Knoblock, and S. Minton. Learning domain-independent string transformation weights for high accuracy object identification. In KDD '02, pages 350-359, New York, NY, USA, 2002. ACM Press.
13. V. N. Vapnik. The nature of statistical learning theory. Statistics for engineering and information science. Springer, New York, 2nd edition, 1999.
14. H. Wache, T. Voegele, U. Visser, H. Stuckenschmidt, G. Schuster, H. Neummann, and S. Huebner. Ontology-based integration of information-a survey of existing approaches. In IJCAI-01 Workshop: Ontologies and Information Sharing, pages 108-117. Seattle, WA, 2001.