An interactive, asymmetric and extensional method for matching conceptual hierarchies

CEUR Workshop Proceedings

Volumn 200, Issue , 2006, Pages

  David, Jérôme ^a   Guillet, Fabrice ^a   Gras, Régis ^a   Briand, Henri ^a  

^a UNIVERSITÉ DE NANTES   (France)

Author keywords

Association rules; Extensional matching; Implication intensity; Matching visualization; Ontology matching

Indexed keywords

CONCEPTUAL HIERARCHY; EXTENSIONAL MATCHING; IMPLICATION INTENSITY; IMPLICATION RULES; INTERACTIVE VISUALIZATION TOOL; KNOWLEDGE ENGINEERS; MATCHING METHODS; ONTOLOGY MATCHING; PROBABILISTIC MODELS; RELEVANT TERMS; SIMILARITY MEASURE; SIMILARITY RELATIONS; TEXTUAL DOCUMENTS;

ASSOCIATION RULES; ONTOLOGY;

INTEROPERABILITY;

EID: 84873537763     PISSN: 16130073     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (17)

1. Doan, A., Madhavan, J., Domingos, P., Halevy, A. In: Ontology Matching : a machine learning approach. Springer-Velag (2004) 397-416
2. Stumme, G., Maedche, A.: FCA-MERGE: Bottom-up merging of ontologies. In: IJCAI. (2001) 225-234
3. Madhavan, J., Bernstein, P.A., Rahm, E.: Generic schema matching with cupid. In: the International Conference on Very Large Data Bases (VLDB'01). (2001) 49-58
4. Melnik, S., Garcia-Molina, H., Rahm, E.: Similarity flooding: A versatile graph matching algorithm and its application to schema matching. In: the 18th International Conference on Data Engineering (ICDE'02), IEEE Computer Society (2002) 117-128
5. Agrawal, R., Imielinski, T., Swami, A.: Mining association rules between sets of items in large databases. In: the 1993 ACM SIGMOD international conference on Management of data, ACM Press (1993) 207-216
6. Gras et al., R.: L'implication statistique, une nouvelle méthode exploratoire de données. La pensée sauvage (1996)
7. Blanchard, J., Kuntz, P., Guillet, F., Gras, R.: 28. In: Implication intensity: from the basic statistical definition to the entropic version. CRC Press (2003) 473-485
8. Do, H., Rahm, E.: Coma - a system for flexible combination of schema matching approaches. In: the International Conference on Very Large Data Bases (VLDB '02). (2002) 610-621
9. Kalfoglou, Y., Schorlemmer, M.: Ontology mapping: the state of the art. Knowedge Engineering Review 18(1) (2003) 1-31
10. Rahm, E., Bernstein, P.A.: A survey of approaches to automatic schema matching. The VLDB Journal 10(4) (2001) 334-350
11. Shvaiko, P., Euzenat, J.: A survey of schema-based matching approaches. Journal on Data Semantics IV 4(LNCS 3730) (2005) 146-171
12. Noy, N., Musen, M.: Anchor-prompt: Using non-local context for semantic matching. In: the Workshop on Ontologies and Information Sharing at the International Joint Conference on Artificial Intelligence (IJCAI). (2001) 63-70
13. Giunchiglia, F., Shvaiko, P., Yatskevich, M.: S-match: an algorithm and an implementation of semantic matching. In: European Semantic Web Symposium. LNCS 3053 (2004) 61-75
14. Castano, S., Ferrara, A., Montanelli, S.: Matching ontologies in open networked systems: Techniques and applications. Journal on Data Semantics 3870(V) (2006) 25-63
15. Castano, S., Antonellis, V.D., Vimercati, S.D.C.D.: Global viewing of heterogeneous data sources. IEEE Transactions on Knowledge and Data Engineering 13(2) (2001)
16. Doan, A., Madhavan, J., Domingos, P., Halevy, A.: Learning to map between ontologies on the semantic web. In: The Eleventh InternationalWWWConference, ACM Press (2002) 662-673
17. Daille, B.: Conceptual structuring through term variations. In Bond, F., Korhonen, A., MacCarthy, D., Villacicencio, A., eds.: ACL 2003 Workshop on Multiword Expressions: Analysis, Acquisition and Treatment. (2003) 9-16