Document Type
Article
Publication Date
2008
Abstract
In this paper we identify some limitations of contemporary information extraction mechanisms in the context of biomedical literature. We present an extraction mechanism that generates structured representations of textual content. Our extraction mechanism achieves this by extracting compound entities, and relationships between them, occuring in text. A detailed evaluation of the relationship and compound entities extracted is presented. Our results show over 62% average precision across 8 relationship types tested with over 82% average precision for compound entity identification1.
Repository Citation
Ramakrishnan, C.,
Mendes, P. N.,
de Gama, R. A.,
Ferreira, G. C.,
& Sheth, A. P.
(2008). Joint Extraction of Compound Entities and Relationships from Biomedical Literature. .
https://corescholar.libraries.wright.edu/knoesis/338
Included in
Bioinformatics Commons, Communication Technology and New Media Commons, Databases and Information Systems Commons, OS and Networks Commons, Science and Technology Studies Commons
Comments
Paper presented at the IEEE/WIC/ACM International Conference on Web Intelligence (WI-08), Sydney, Australia, December 9-12, 2008.