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UC3M: A kernel-based approach to identify and classify DDIs in bio-medical texts.

. SemEval@NAACL-HLT, page 617-621. The Association for Computer Linguistics, (2013)

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An Approach for Detecting Modality and Negation in Texts by Using Rule-based Techniques., , , , and . CLEF (Online Working Notes/Labs/Workshop), volume 1178 of CEUR Workshop Proceedings, CEUR-WS.org, (2012)Prototipo buscador de información médica en corpus multilingües y extractor de información sobre fármacos., , and . Proces. del Leng. Natural, (2012)A Web Prototype for Detecting Chemical Compounds and Drugs., , , , and . SWAT4LS, volume 1114 of CEUR Workshop Proceedings, CEUR-WS.org, (2013)UEM-UC3M: An Ontology-based named entity recognition system for biomedical texts., and . SemEval@NAACL-HLT, page 622-627. The Association for Computer Linguistics, (2013)DDIExtractor: A Web-Based Java Tool for Extracting Drug-Drug Interactions from Biomedical Texts., , and . NLDB, volume 6716 of Lecture Notes in Computer Science, page 274-277. Springer, (2011)Combining dictionaries and ontologies for drug name recognition in biomedical texts., , and . DTMBIO, page 27-30. ACM, (2013)UC3M: A kernel-based approach to identify and classify DDIs in bio-medical texts.. SemEval@NAACL-HLT, page 617-621. The Association for Computer Linguistics, (2013)UEM-UC3M: An Ontology-based named entity recognition system for biomedical texts., and . Proceedings of the 7th International Workshop on Semantic Evaluation (SemEval 2013), (2013)