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Resolving ambiguity in biomedical text to improve summarization

, , and . Information Processing & Management, 48 (4): 755 - 766 (2012)
DOI: http://dx.doi.org/10.1016/j.ipm.2011.09.005

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Enriched Semantic Graphs for Extractive Text Summarization., , and . CAEPIA, volume 9868 of Lecture Notes in Computer Science, page 217-226. Springer, (2016)Resolving ambiguity in biomedical text to improve summarization, , and . Information Processing & Management, 48 (4): 755 - 766 (2012)NIL_UCM: Extracting Drug-Drug interactions from text through combination of sequence and tree kernels., and . SemEval@NAACL-HLT, page 644-650. The Association for Computer Linguistics, (2013)Evaluation of a System for Personalized Summarization of Web Contents., , and . User Modeling, volume 3538 of Lecture Notes in Computer Science, page 453-462. Springer, (2005)A semantic graph-based approach to biomedical summarisation., , and . Artif. Intell. Medicine, 53 (1): 1-14 (2011)Inferring the Scope of Negation and Speculation Via Dependency Analysis., , , , and . Proces. del Leng. Natural, (2011)Adapting a Generic Platform for Poetry Generation to Produce Spanish Poems., , , and . ICCC, page 63-71. computationalcreativity.net, (2014)Development and Use of an Evaluation Collection for Personalisation of Digital Newspapers., , , and . LREC, European Language Resources Association, (2010)Improving Information Extraction from Wikipedia Texts using Basic English., , , and . LREC, European Language Resources Association (ELRA), (2016)Adaptive text generation based on emotional lexical choice., , and . Interacción, page 20:1-20:2. ACM, (2014)