Abstract
One of the main problems in research on automatic summarization is the inaccurate semantic interpretation of the source. Using specific domain knowledge can considerably alleviate the problem. In this paper, we introduce an ontology-based extractive method for summarization. It is based on mapping the text to concepts and representing the document and its sentences as graphs. We have applied our approach to summarize biomedical literature, taking advantages of free resources as UMLS. Preliminary empirical results are presented and pending problems are identified.
Cite
CITATION STYLE
Morales, L. P., Esteban, A. D., & Gervás, P. (2008). Concept-graph based biomedical automatic summarization using ontologies. In Proceedings of the 3rd Textgraphs Workshop on Graph-Based Algorithms for Natural Language Processing, TextGraphs 2008 (pp. 53–56). Association for Computational Linguistics and Chinese Language Processing. https://doi.org/10.3115/1627328.1627336
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