Discovering Concept Mappings by Similarity Propagation among Substructures
Concept matching is important when heterogeneous data sources are to be merged for the purpose of knowledge sharing. It has many useful applications in areas such as schema matching, ontology matching, scientific knowledge management, e-commerce, enterprise application integration, etc. With the des...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Book Chapter |
| Published: |
Springer
2010
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/6865 |
| _version_ | 1848745200593141760 |
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| author | Pan, Qi Hadzic, Fedja Dillon, Tharam S. |
| author2 | Colin Fyfe |
| author_facet | Colin Fyfe Pan, Qi Hadzic, Fedja Dillon, Tharam S. |
| author_sort | Pan, Qi |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Concept matching is important when heterogeneous data sources are to be merged for the purpose of knowledge sharing. It has many useful applications in areas such as schema matching, ontology matching, scientific knowledge management, e-commerce, enterprise application integration, etc. With the desire of knowledge sharing and reuse in these fields, merging commonly occurs among different organizations where the knowledge describing the same domain is to be matched. Due to the different naming conventions, granularity and the use of concepts in different contexts, a semantic approach to this problem is preferred in comparison to syntactic approach that performs matches based upon the labels only. We propose a concept matching method that initially does not consider labels when forming candidate matches, but rather utilizes structural information to take the context into account and detect complex matches. Real world knowledge representations (schemas) are used to evaluate the method. |
| first_indexed | 2025-11-14T06:13:35Z |
| format | Book Chapter |
| id | curtin-20.500.11937-6865 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T06:13:35Z |
| publishDate | 2010 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-68652022-12-09T07:12:36Z Discovering Concept Mappings by Similarity Propagation among Substructures Pan, Qi Hadzic, Fedja Dillon, Tharam S. Colin Fyfe Peter Tino Darryl Charles Cesar Garcia-Osorio HujunYin schema matching concept matching tree mining Concept matching is important when heterogeneous data sources are to be merged for the purpose of knowledge sharing. It has many useful applications in areas such as schema matching, ontology matching, scientific knowledge management, e-commerce, enterprise application integration, etc. With the desire of knowledge sharing and reuse in these fields, merging commonly occurs among different organizations where the knowledge describing the same domain is to be matched. Due to the different naming conventions, granularity and the use of concepts in different contexts, a semantic approach to this problem is preferred in comparison to syntactic approach that performs matches based upon the labels only. We propose a concept matching method that initially does not consider labels when forming candidate matches, but rather utilizes structural information to take the context into account and detect complex matches. Real world knowledge representations (schemas) are used to evaluate the method. 2010 Book Chapter http://hdl.handle.net/20.500.11937/6865 Springer restricted |
| spellingShingle | schema matching concept matching tree mining Pan, Qi Hadzic, Fedja Dillon, Tharam S. Discovering Concept Mappings by Similarity Propagation among Substructures |
| title | Discovering Concept Mappings by Similarity Propagation among Substructures |
| title_full | Discovering Concept Mappings by Similarity Propagation among Substructures |
| title_fullStr | Discovering Concept Mappings by Similarity Propagation among Substructures |
| title_full_unstemmed | Discovering Concept Mappings by Similarity Propagation among Substructures |
| title_short | Discovering Concept Mappings by Similarity Propagation among Substructures |
| title_sort | discovering concept mappings by similarity propagation among substructures |
| topic | schema matching concept matching tree mining |
| url | http://hdl.handle.net/20.500.11937/6865 |