Extracción no supervisada de relaciones entre medicamentos y efectos adversos.
Andrés Duque Fernandez, Juan Martinez-Romo, Lourdes Araujo
Procesamiento del Lenguaje Natural 55: 83-90 (2015)

In this work we present preliminary results obtained by a new unsupervised technique
for extracting relations between drugs and adverse drug reactions. The identification
of those relations is achieved using a knowledge representation model that generates pairs of
entities and assigns them a specific weight, depending on the statistical significance of their
co-occurrence in the same document. This model may subsequently be transformed into a
graph. The system has been evaluated over the reference ADE corpus, obtaining promising
results, since its effectiveness is quite higher than that obtained by a standard basline. First
tests also show a high potential for inducing new knowledge.