Abstract
A graphical language addresses the need to communicate medical information in a synthetic way. Medical concepts are expressed by icons conveying fast visual information about patients’ current state or about the known effects of drugs. In order to increase the visual language’s acceptance and usability, a natural language generation interface is currently developed. In this context, this paper describes the use of an informatics method – graph transformation – to prepare data consisting of concepts in an OWL-DL ontology for use in a natural language generation component. The OWL concept may be considered as a star-shaped graph with a central node. The method transforms it into a graph representing the deep semantic structure of a natural language phrase. This work may be of future use in other contexts where ontology concepts have to be mapped to half-formalized natural language expressions.
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Lamy, J.-B., Duclos, C., Bar-Hen, A., Ouvrard, P., Venot, A.: An iconic language for the graphical representation of medical concepts. BMC Med. Inform. Decis. Mak. 8 (16) (2008)
Welty, C., McGuinness, D.L., Smith, M.K.: OWL web ontology language guide. W3C Recommandation. W3C (2004), http://www.w3.org/TR/owl-guide/
Wilcock, G.: Talking OWLs: Towards an ontology verbalizer. In: Proc. ISWC Workshop on Human Language Technology for the Semantic Web and Web Services, pp. 109–112 (2003)
Hewlett, D., Kalyanpur, A., Kolovski, V., Halaschek-Wiener, C.: Effective NL paraphrasing of ontologies on the semantic web. In: Proc. ISWC Workshop on End User Semantic Web Interaction, vol. 172. CEUR-WS.org (2005)
Bontcheva, K., Wilks, Y.: Automatic report generation from ontologies: the MIAKT approach. In: Meziane, F., Métais, E. (eds.) NLDB 2004. LNCS, vol. 3136, pp. 324–335. Springer, Heidelberg (2004)
Sowa, J.: Conceptual structures: information processing in mind and machine. Addison Wesley, New York (1984)
Rector, A.L., Bechhofer, S., Goble, C.A., Horrocks, I., Nowlan, W.A., Solomon, W.D.: The GRAIL concept modelling language for medical terminology. Artif. Intell. Med. 9(2), 139–171 (1997)
Ehrig, H., Habel, A., Kreowski, H.J.: Introduction to Graph Grammars with Applications to Semantic Networks. Comput. Math. Appl. 23(6-9), 557–572 (1992)
Schürr, A., Winter, A.J., Zündorf, A.: Graph grammar engineering with PROGRES. In: Botella, P., Schäfer, W. (eds.) ESEC 1995. LNCS, vol. 989, pp. 219–234. Springer, Heidelberg (1995)
Blostein, D., Fahmy, H., Grbavec, A.: Issues in the practical use of graph rewriting. In: Cuny, J., Engels, G., Ehrig, H., Rozenberg, G. (eds.) Graph Grammars 1994. LNCS, vol. 1073, pp. 38–55. Springer, Heidelberg (1996)
Schabes, Y., Abeillé, A., Joshi, A.K.: Parsing strategies with ‘lexicalized’ grammars: application to Tree Adjoining Grammars. In: COLING 1988: Proc. 12th International Conference on Computational Linguistics, Budapest, August 22-27, pp. 578–583 (1988)
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Vaillant, P., Lamy, JB. (2014). Using Graph Transformation Algorithms to Generate Natural Language Equivalents of Icons Expressing Medical Concepts. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2014. Lecture Notes in Computer Science(), vol 8655. Springer, Cham. https://doi.org/10.1007/978-3-319-10816-2_43
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DOI: https://doi.org/10.1007/978-3-319-10816-2_43
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