Extraction of definitional contexts from restricted domains by measuring synthetic judgements and word relevance
Por:
Aguilar C., Acosta O.
Publicada:
1 ene 2015
Categoría:
Computer Science (miscellaneous)
Resumen:
In this article we present an ongoing work for extracting conceptual information from specialized-domain texts. Concepts are forms of dividing the world in classes and they are the fundamental pieces for constructing ontologies. In this sense, ontology learning is the (semi-) automatic support for constructing an ontology. Input data are required for the ontology learning and this data are the basic source from which to learn the relevant concepts for a domain, their definitions as well the relations holding between them. With this necessity in mind, we propose here a methodology that takes into account the level of synthetic judgements and word relevance in a sentence in order to filter out and rank sentences. Sentences with high relevance and low level of synthetic judgements should have at least a predicative verb characteristic of analytical definitions for being good candidates.
Filiaciones:
Aguilar C.:
Pontificia Universidad Católica de Chile, Santiago, Chile
Acosta O.:
Pontificia Universidad Católica de Chile, Santiago, Chile
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