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Pedro Hípola, José A Senso, Amed Leiva-Mederos, Sandor Domínguez-Velasco (2014) Ontology-based text summarization. The case of Texminer, Library Hi Tech 32(2), p. 229-248

DOI10.1108/LHT-01-2014-0005
ResumenPurpose This study looks into the latest advances in ontology-based text summarization systems, with emphasis on the methodologies of a socio-cognitive approach, the structural discourse models and the ontology-based text summarization systems. Design/methodology/approach The paper analyzes the main literature in this field and presents the structure and features of Texminer, a software that facilitates summarization of texts on Port and Coastal Engineering. Texminer entails a combination of several techniques, including: socio-cognitive user models, Natural Language Processing (NLP), disambiguation and ontologies. After processing a corpus, the system was evaluated using as a reference various clustering evaluation experiments conducted by Arco (Arco, 2008) and Hennig (Hennig et. al., 2008). The results were checked with a Support Vector Machine, Rouge metrics, the F-Measure and calculation of precision and recall. Findings The experiment illustrates the superiority of abstracts obtained through the assistance of ontology-based techniques. Originality/value We were able to corroborate that the summaries obtained using Texminer are more efficient than those derived through other systems whose summarization models do not use ontologies to summarize texts. Thanks to ontologies, main sentences can be selected with a broad rhetorical structure, especially for a specific knowledge domain.
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