@article {10.3844/jcssp.2018.945.956,
article_type = {journal},
title = {Enhancing Brazilian Portuguese Textual Entailment Recognition with a Hybrid Approach},
author = {de Barcelos Silva , Allan and Rigo, Sandro José},
volume = {14},
number = {7},
year = {2018},
month = {Jul},
pages = {945-956},
doi = {10.3844/jcssp.2018.945.956},
url = {https://thescipub.com/abstract/jcssp.2018.945.956},
abstract = {Previous work on textual entailment has not fully exploited aspects of deep linguistic relations, which have been shown as containing important information for entailment identification. In this study, we present a new method to compute semantic textual similarity between two sentences. Our proposal relies on the integration of a set of deep linguistic relations, lexical aspects and distributed representational resources. We used our method with a large set of annotated data available from the ASSIN Workshop in the PROPOR 2016 event. The achieved results score among the best-known results in the literature. A perceived advantage of our approach is the ability to generate good results even with a small corpus on training tasks.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}