Application of Domain Ontologies to Natural Language Processing: A Case Study for Drug-Drug Interactions

María Herrero-Zazo, Isabel Segura-Bedmar, Janna Hastings and Paloma Martínez
Additional contact information
María Herrero-Zazo: Department of Computer Science, Universidad Carlos III de Madrid, Madrid, Spain
Isabel Segura-Bedmar: Department of Computer Science, Universidad Carlos III de Madrid, Madrid, Spain
Janna Hastings: European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
Paloma Martínez: Department of Computer Science, Universidad Carlos III de Madrid, Madrid, Spain

International Journal of Information Retrieval Research (IJIRR), 2015, vol. 5, issue 3, 19-38

Abstract: Natural Language Processing (NLP) techniques can provide an interesting way to mine the growing biomedical literature, and a promising approach for new knowledge discovery. However, the major bottleneck in this area is that these systems rely on specific resources providing the domain knowledge. Domain ontologies provide a contextual framework and a semantic representation of the domain, and they can contribute to a better performance of current NLP systems. However, their contribution to information extraction has not been well studied yet. The aim of this paper is to provide insights into the potential role that domain ontologies can play in NLP. To do this, the authors apply the drug-drug interactions ontology (DINTO) to named entity recognition and relation extraction from pharmacological texts. The authors use the DDI corpus, a gold-standard for the development and evaluation of IE systems in this domain, and evaluate their results in the framework of the last SemEval-2013 DDI Extraction task.

Date: 2015
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 018/IJIRR.2015070102 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jirr00:v:5:y:2015:i:3:p:19-38

Access Statistics for this article

International Journal of Information Retrieval Research (IJIRR) is currently edited by Zhongyu Lu

More articles in International Journal of Information Retrieval Research (IJIRR) from IGI Global
Bibliographic data for series maintained by Journal Editor ().