Schema and constraints-based matching and merging of Topic Maps

Information Processing and Management

Volumn 43, Issue 4, 2007, Pages 930-945

  Kim, Jung Mn ^a   Shin, Hyopil ^a   Kim, Hyoung Joo ^a  

^a Seoul National University   (South Korea)

Author keywords

Ontology matching; Ontology merging; Topic Maps matching; Topic Maps merging

Indexed keywords

ONTOLOGY MATCHING; ONTOLOGY MERGING; TOPIC MAPS MATCHING; TOPIC MAPS MERGING;

COMPUTATIONAL METHODS; CONSTRAINT THEORY; LINGUISTICS; ONTOLOGY; SEMANTIC WEB; SYNTACTICS;

PATTERN MATCHING;

EID: 33947121333     PISSN: 03064573     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ipm.2006.08.012     Document Type: Article

References (24)

1. Berman B.L. Library of congress subject headings in philosophy: A thesaurus (2001), Philosophy Document Center. 0-912632-64-X
2. Beneventano, D., Bergamaschi, S., Guerra, F., & Vincini, M. (2001). The MO MIS approach to information integration. In IEEE and AAAI International Conference on Enterprise Information Systems ,pp. 194-198, SetubaL Portugal.
3. Biezunski, M., Bryan, M., & Newcomb, S. (2002). ISO/IEC 13250 TopicMaps. http/www1.y12.doe.gov/capabihties/sgm1/sc34/document/0322.htm.
4. Bouquet, P., Serafini, L., & Zanobini, S. (2003). Semantic coordination: a new approach and an application. In Proceedings of ISWC (pp. 130-145), Sanibel Island, Florida, USA.
5. Do, H. H., & Rahm, E. (2002). COMA - a system for flexible combination of schema matching approaches, In Proceedings of VLDB (pp. 610-621).
6. Doan, A., Domingos, P., & Halevy, A. (2001). Reconciling schemas of disparate data sources: a machine-learning approach. In Proceedings ACM SIGMOD Conference.
7. Durusau, P., Newcomb, S., & Barta, R. (2006). Topic Maps - Reference Model ISO/IEC JTC1/SC34, Version 6.0, http://www.isotopicmaps.org/tmrm.
8. Ehrig, M., & Staab, S. (2004). QOM: quick ontology matching. In Proceedings of ISWC (pp. 683-697). Hiroshima, Japan.
9. Garshol L.M., and Moore G. Topic maps data model (2005).
10. Giunchglia F., and Shvaiko P. Semantic matching. In the Knowledge Engineering Review Journal 18 3 (2003) 265-280
11. Kalfoglou, Y., & Schorlemmer, M. (2002). Information-flow-based ontology matching. In Proceedings of the 1st international conference on ontologies, database and application of semantics (pp. 1132-1151). Irvine, California, USA.
12. Kim J.M., Choi B.I., and Kim H.J. Building a philosophy ontology based on contents of philosophical texts. Korea Information Science Society 11 4 (2004) 275-283
13. Lassila, O., & Swick, R. R. (1999). Resource Description Framework (RDF) Model and Syntax Specification. W3C Recommendation. URL: http://www.w3.org/TR/REV-rdf-syntax.
14. Li W., Clifton C., and Liu S. Database integration using neural network: implementation and experiens. Knowledge Information Systems 2 1 (2000) 73-96
15. Madhavan, J., Bernstein, P., & Rahm, E. (2001). Generic Schema Matching with Cupid. In Proceedings of VLDB (pp. 49-58).
16. Maicher, L., & Witschel, H. F. (2004). Merging of distributed topic maps based on the subject identity measure (SIM) approach. In Proceedings of Berliner XML tags (pp. 301-307).
17. McGuinness, D.L., & Harmeba (2003). OWL Web Ontology Language Overview. W3C Recommendation, http://www.w3.org/TR/ow1-featares/.
18. Melnik, S., Garcia-Molina, H., & Rahm, E. (2002). Similarity flooding: a versatile graph matching algorithm. In Proceedings of ICDE (pp. 117-128). San Jose, California, USA.
19. Noy, N., & Musen, M. (2000). PROMPT: algorithm and tool for automated ontology merging and alignment. In Proceedings of the national conference on artificial intelligence (AAAI) (pp. 450-455). Austin, TX, USA.
20. Noy, N., & Musen, M. (2001). Anchor-PROMPT: using non-local context for semantic matching. In Proceedings of the workshop on ontologies and information sharing at the international joint conference on artificial intelligence (IJCAI) (pp. 63-70). Seattle, WA, USA.
21. Pepper, S., & Moore, G. (2001). XML Topic Maps (XTM) 1.0, Topic Maps.Org. http://www.topicmaps.org/xtm/.
22. Rahm E., and Bernstein P. On matching schemas automatically. VLDB Journal 10 4 (2001) 334-350
23. Shvaiko, P., & Euzenat, J. (2004). A survey of schema-based matching approaches. University of Trento, Technical Report #DIT-04-087 (pp. 1-22).
24. Stumme, G., & Madche, A. (2001). FCA-merge: bottom-up merging of ontologies. In Proceedings of 17th international joint conference on artificial intelligence (IJCAI) (pp. 225-234). Seattle, Washington, USA.