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Article: Pattern matching for heterogeneous geodata sources using attributed relational graph and probabilistic relaxation
Title | Pattern matching for heterogeneous geodata sources using attributed relational graph and probabilistic relaxation |
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Authors | |
Issue Date | 2007 |
Citation | Photogrammetric Engineering and Remote Sensing, 2007, v. 73, n. 6, p. 663-670 How to Cite? |
Abstract | Information retrieval and intelligent search among heterogeneous data sources still continue to be challenging tasks. In this study, an attributed relational graph was employed to model the semantic information of heterogeneous geodata sources. Based on the attributed relational graphs, probabilistic relaxation was employed for pattern matching between different data sources. The initial probability and compatibility coefficients were calculated based on the combined evidence from semi-structured geodata sources and the characteristics of discrete and categorical variables. Experiments on automatic pattern matching were carried out and the results demonstrated the effectiveness of the proposed approach in element mapping between heterogeneous data sources. © 2007 American Society for Photogrammetry and Remote Sensing. |
Persistent Identifier | http://hdl.handle.net/10722/330088 |
ISSN | 2023 Impact Factor: 1.0 2023 SCImago Journal Rankings: 0.309 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Yi, Shanzhen | - |
dc.contributor.author | Huang, Bo | - |
dc.contributor.author | Wang, Cheng | - |
dc.date.accessioned | 2023-08-09T03:37:42Z | - |
dc.date.available | 2023-08-09T03:37:42Z | - |
dc.date.issued | 2007 | - |
dc.identifier.citation | Photogrammetric Engineering and Remote Sensing, 2007, v. 73, n. 6, p. 663-670 | - |
dc.identifier.issn | 0099-1112 | - |
dc.identifier.uri | http://hdl.handle.net/10722/330088 | - |
dc.description.abstract | Information retrieval and intelligent search among heterogeneous data sources still continue to be challenging tasks. In this study, an attributed relational graph was employed to model the semantic information of heterogeneous geodata sources. Based on the attributed relational graphs, probabilistic relaxation was employed for pattern matching between different data sources. The initial probability and compatibility coefficients were calculated based on the combined evidence from semi-structured geodata sources and the characteristics of discrete and categorical variables. Experiments on automatic pattern matching were carried out and the results demonstrated the effectiveness of the proposed approach in element mapping between heterogeneous data sources. © 2007 American Society for Photogrammetry and Remote Sensing. | - |
dc.language | eng | - |
dc.relation.ispartof | Photogrammetric Engineering and Remote Sensing | - |
dc.title | Pattern matching for heterogeneous geodata sources using attributed relational graph and probabilistic relaxation | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.14358/PERS.73.6.663 | - |
dc.identifier.scopus | eid_2-s2.0-34249811508 | - |
dc.identifier.volume | 73 | - |
dc.identifier.issue | 6 | - |
dc.identifier.spage | 663 | - |
dc.identifier.epage | 670 | - |
dc.identifier.isi | WOS:000246871900007 | - |