OntoFIS as a NLP resource in the drug-therapy domain: Design issues and solutions applied

0Citations
Citations of this article
2Readers
Mendeley users who have this article in their library.
Get full text

Abstract

In the Health domain, and specifically in the drug-therapy domain, in order to improve the access to the information of different types of users, several informational resources, semantically annotated, are under development. One of the existing development lines is oriented to reusing the effort spent on the design of the existing resources on the Web and obtaining knowledge-based resources for natural language processing (NLP) tasks. In this line, OntoFIS was designed as a NLP resource aimed at filling the gap of multilingual knowledge-based resources within the domain. The design process used for building OntoFIS merges the best approaches of several ontology design methodologies. However, given the characteristics of the drug-therapy domain, whose needs of knowledge are very precise, the process of formalisation of the domain knowledge led to a set of issues. Thus, this paper discusses the main issues found and the solutions analysed and applied in each case. © 2011 Springer-Verlag.

Cite

CITATION STYLE

APA

Romá-Ferri, M. T., Hermida, J. M., & Palomar, M. (2011). OntoFIS as a NLP resource in the drug-therapy domain: Design issues and solutions applied. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6716 LNCS, pp. 125–136). https://doi.org/10.1007/978-3-642-22327-3_12

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free