An Approach for Ontology Building from Text Supported by NLP Techniques (original) (raw)
Abstract
In this work, we present an approach to simplify Knowledge Acquisition Processes (KAPs) by means of extracting knowledge directly from natural language texts. The ultimate goal is to acquire knowledge straight from experts’ language. This approach uses a morphologic analyzer to improve the setting-in-a-context between knowledge elements (e.g., concepts and attributes). Another objective is achieving language independency. Here, the knowledge acquired from texts is represented by means of ontologies.
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Authors and Affiliations
- Departamento de Ingeniería de la Información y las Comunicaciones, Universidad de Murcia, Campus de Espinardo, CP 30071, Murcia, Spain
Rafael Valencia-García, Pedro José Vivancos Vicente, Rodrigo Martínez-Béjar & Francisco García Sánchez - Facultad de Informática y Matemática, Universidad de Holguín, Av. XX Aniversario s/n, CP 80100, Holguín, Cuba
Dagoberto Castellanos Nieves - Departamento de Informática y Sistemas, Facultad de Informática, Universidad de Murcia, Campus de Espinardo, CP 30071, Murcia, Spain
Jesualdo Tomás Fernández Breis
Authors
- Rafael Valencia-García
- Dagoberto Castellanos Nieves
- Pedro José Vivancos Vicente
- Jesualdo Tomás Fernández Breis
- Rodrigo Martínez-Béjar
- Francisco García Sánchez
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Editors and Affiliations
- Departamento de Lenguajes y Ciencias de la Computación, Universidad de Málaga,
Ricardo Conejo - Facultad de Informática, Dept. Lenguajes y Sistemas Informáticos Codigo, EPV/EHU, Postal 649, 20080, San Sebastian, Spain
Maite Urretavizcaya - Departamento de Lenguajes y Ciencias de la Computación, Universidad de Málaga, Campus de Teatinos s/n, 29079, Málaga, SPAIN
José-Luis Pérez-de-la-Cruz
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Valencia-García, R., Castellanos Nieves, D., Vivancos Vicente, P.J., Fernández Breis, J.T., Martínez-Béjar, R., García Sánchez, F. (2004). An Approach for Ontology Building from Text Supported by NLP Techniques. In: Conejo, R., Urretavizcaya, M., Pérez-de-la-Cruz, JL. (eds) Current Topics in Artificial Intelligence. TTIA 2003. Lecture Notes in Computer Science(), vol 3040. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25945-9\_13
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- DOI: https://doi.org/10.1007/978-3-540-25945-9\_13
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