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UC3M: A kernel-based approach to identify and classify DDIs in bio-medical texts.
Daniel Sanchez-Cisneros
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Paper Details:
Month: June
Year: 2013
Location: Atlanta, Georgia, USA
Venue:
*SEMEVAL |
Citations
URL
SemEval-2013 Task 9 : Extraction of Drug-Drug Interactions from Biomedical Texts (DDIExtraction 2013)
Isabel Segura-Bedmar
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Paloma Martínez
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María Herrero-Zazo
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http://www.biocreative.org/
http://2013.bionlp-st.org/
http://www.cs.york.ac.uk/semeval-2013/task9/
http://www.drugbank.ca/
http://labda.inf.uc3m.es/DDIExtraction2011/
http://nlp.stanford.edu/software/lex-parser.shtml
http://gate.ac.uk
http://www.whocc.no/atc_ddd_index/
http://hlt.fbk.eu/en/technology/jSRE
http://labda.inf.uc3m.es/multimedica/
Field Of Study
Linguistic Trends
Ontologies
Task
Tagging
Information Extraction
Biomedical
Language
English
Dataset
Biomedical Texts
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