An Improved Semantic Schema Matching Approach
محورهای موضوعی : Embedded Systems
Zahra Sheikhnajdy
1
(Department of Computer Engineering, Science and
Research Branch, Islamic Azad University, Khouzestan)
Mehran Mohsenzadeh
2
(Department of Computer Engineering, Science and Research Branch, Islamic Azad University)
Mashalah Abbasi Dezfuli
3
(Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Khouzestan)
کلید واژه: schema matching, schema integration, Ontology, RDF Schema, element level matcher, structural level matcher,
چکیده مقاله :
Schema matching is a critical step in many applications, such as data warehouse loading, Online Analytical Process (OLAP), Data mining, semantic web [2] and schema integration. This task is defined for finding the semantic correspondences between elements of two schemas. Recently, schema matching has found considerable interest in both research and practice. In this paper, we present a new improved solution for schema matching problem. An improvement hybrid semantic schema matching algorithm which semi automatically finds matching between two data representation schemas is introduced. The algorithm finds mappings based on the hierarchical organization of the elements of a term WordNet dictionary.
[1] Manakanatas D., Plexousakis D., “A Tool for Semi-Automated Semantic Schema Mapping: Design and implementation”, International Workshop Data Integration and the Semantic Web, pp. 290-306, June 5-9, 2009.
[2] Dou D., Qin H., LePendu P., “ontograte: towards automatic integration for relational databases and the semantic web through an ontology-based framework”, International Journal of Semantic Computing Vol. 4, No. 1 pages 123–151, 2010.
[3] Shvaiko P., Giunchiglia F., Yatskevich M.,” semantic matching with s-match”, Springer, 2009.
[4] Partyka J., Khan L., Thuraisingham B., “Semantic Schema Matching Without Shared Instances”, IEEE International Conference on Semantic Computing, 2009.
[5] Doan A., Domingos P., Halevy A., “Reconciling schemas of disparate data sources: a machine-learning approach”, SIGMOD conference, pages 09–520, 2001.
[6] Aumueller D., Do H.H., Massmann S., Rahm E., “Schema and Ontology Matching with COMA++”, Proc. ACM SIGMOD international conference on Management of data, pages 906-908, 2005.
[7] Do H. H., Rahm E., “COMA – A System for Flexible Combination of Schema Matching Approach”, Proc. VLDB, pages 610-621, 2002.
[8] Do H. H., Rahm E., Melnik S., “Comparison of Schema Matching Evaluations”. Proc. GI – Workshop “Web and Databases”, Oct. 2002.
[9] Yatskevich M., “Preliminary Evaluation of Schema Matching Systems”, Technical Report DIT-03-028, May 2003.
[10] Madhavan J., Bernstein P.A., Rahm E., “Generic Schema Matching with Cupid”, Proc. In VLDB : Proceedings of the 27th International Conference on Very Large Data Bases, pages 49-58, San Francisco, CA, USA, 2001.
[11] WordNet a Lexical Database for the English Language, http://wordnet.princeton.edu/
[12] Saake G., Sattler K.U., Conrad S., “Rule-based schema matching for Ontology-based mediators”, Elsevier, 2005.
[13] Rahm E., Bernstein P., “A survey of approaches to automatic schema matching”, VLDB J. 10 (4), pages 334–350, 2001.
[14] Evermann J., “Theories of Meaning in Schema Matching: A Review”, Journal of Database Management, 19(3), pages 55-82, July-September 2008.
[15] Teymoorian F., Mohsenzadeh M., “English-Persian Text Retrieval Using Concept Graph”, IEEE International Conference on Computer Science and Information Technology (IACSIT), Singapore, 2009.
[16] Chiticariu L., Mauricio A. Andez H., Kolaitis P. G., Popa L., “Semi-Automatic Schema Integration in Clio”, ACM – September, pages 23-28, 2007.
[17] Milo T., Zohar S., “Using schema matching to simplify heterogeneous data translation”, in: Int. Conference on Very Large Data Bases (VLDB) 98, pages 122–133, 1998.
[18] Soltanpoor R., Mohsenzadeh M., Mohaqeqi M., "Using concept graph and Naive Bayes to improve the classification of unknown documents", IEEECS, Conference on Information and Software Engineering, India, 2010.
[19] Teymoorian F., Mohsenzadeh M., Seyyedi M., "Using Concept Graph to Increase Bilingual Text Retrieval Precision", IEEE International Conference on Digital Ecosystems and Technologies, Istanbul, Turkey, 2009.
[20] Evermann J., “Theories of Meaning in Schema Matching: A Review”, Journal of Database Management, 19(3), pages 55-82, July-September 2008
