Inferring Relations and An notations in Semantic Network: Application to Radiology
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| Formato: | Artículo científico |
| Lenguaje: | en |
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Instituto Politécnico Nacional
2014
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| _version_ | 1876456245220605952 |
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| author | Lionel Ramadier |
| author_facet | Lionel Ramadier |
| contents | Inferring Relations and An notations in Semantic Network: Application to Radiology Lionel Ramadier Manel Zarrouk Mathieu Lafourcade Antoine Micheau Computación radiology Relation inference relation annotation lexical semantic network Domain-specific ontologies are invaluable despite many challenges associated with their development. In most cases, domain knowledge bases are built with very limited scope without considering the benefits of plunging domain knowledge to a general ontology. Furthermore, most existing resources lack meta-information about association strength (weights) and annotations (frequency information like frequent , rare , etc. or relevance information like pertinent or irrelevant ). In this paper, we present a semantic resource for radiology built over an existing general semantic lexical network (JeuxDeMots). This network combines weight and annotations on typed relations between terms and concepts. Some inference mechanisms are applied to the network to improve its quality and coverage. We extend this mechanism to relation annotation. We describe how annotations are handled and how they improve the network by imposing new constraints especially those founded on medical knowledge. 2014 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61532067004 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.3 Vol.18 |
| format | Artículo científico |
| id | redalyc_61532067004 |
| institution | Redalyc |
| language | en |
| publishDate | 2014 |
| publisher | Instituto Politécnico Nacional |
| spellingShingle | Inferring Relations and An notations in Semantic Network: Application to Radiology Lionel Ramadier Computación radiology Relation inference relation annotation lexical semantic network Inferring Relations and An notations in Semantic Network: Application to Radiology Lionel Ramadier Manel Zarrouk Mathieu Lafourcade Antoine Micheau Computación radiology Relation inference relation annotation lexical semantic network Domain-specific ontologies are invaluable despite many challenges associated with their development. In most cases, domain knowledge bases are built with very limited scope without considering the benefits of plunging domain knowledge to a general ontology. Furthermore, most existing resources lack meta-information about association strength (weights) and annotations (frequency information like frequent , rare , etc. or relevance information like pertinent or irrelevant ). In this paper, we present a semantic resource for radiology built over an existing general semantic lexical network (JeuxDeMots). This network combines weight and annotations on typed relations between terms and concepts. Some inference mechanisms are applied to the network to improve its quality and coverage. We extend this mechanism to relation annotation. We describe how annotations are handled and how they improve the network by imposing new constraints especially those founded on medical knowledge. 2014 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61532067004 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.3 Vol.18 |
| title | Inferring Relations and An notations in Semantic Network: Application to Radiology |
| topic | Computación radiology Relation inference relation annotation lexical semantic network |
| url | https://www.redalyc.org/articulo.oa?id=61532067004 |