Human Language Technologies: Key Issues for Representing Knowledge from Textual Information

Ontologies are appropriate structures for capturing and representing the knowledge about a domain or task. However, the design and further population of them are both di_cult tasks, normally addressed in a manual or in a semi-automatic manner. The goal of this article is to de_ne and extend a task-oriented ontology schema that semantically represents the information contained in texts. This information can be extracted using Human Language Technologies, and throughout this work, the whole process to design such ontology schema is described. Then, we also describe an algorithm to automatically populate ontologies based our Human Language Technology oriented schema, avoiding the unnecessary duplication of instances, and having as a result the required information in a more compact and useful format ready to exploit. Tangible results are provided, such as permanent online access points to the ontology schema, an example bucket (i.e. ontology instance repository) based on a real scenario, and a documentation Web page.

Autores: 
Gutiérrez, Yoan
Lloret, Elena
Gomez, José M.
Tipo de publicación: 
Revista
Nombre de la revista: 
Journal of Universal Computer Science
Nombre del libro: 
Journal of Universal Computer Science
Volumen: 
24
Número: 
11
ISSN: 
0948-695x
0948-6968
Revisión por pares: 
Internacional: 
Publicable: