Detecting semantic difference: a new model based on knowledge and collocational association

Semantic discrimination among concepts is a daily exercise for humans when using natural languages. For example, given the words, airplane and car, the word flying can easily be thought and used as an attribute to differentiate them. In this study, we propose a novel automatic approach to detect whether an attribute word represents the difference between two given words. We exploit a combination of knowledge-based and co-occurrence features (collocations) to capture the semantic difference between two words in relation to an attribute. The features are scores that are defined for each pair of words and an attribute, based on association measures, n-gram counts, word similarity, and Concept-Net relations. Based on these features we designed a system that run several experiments on a SemEval-2018 dataset. The experimental results indicate that the proposed model performs better, or at least comparable with, other systems evaluated on the same data for this task.

Citation

Taslimipoor, S., Corpas Pastor, G. and Rohanian, O. (2020) Detecting semantic difference: a new model based on knowledge and collocational association, in Corpas Pastor, G. and Colson, J.P. (eds) Computational Phraseology. John Benjamins, pp. 312–324.

Type

Chapter in book

Language

en

Description

This is an accepted manuscript of an article published by John Benjamins Publishing Company in Computational Phraseology edited by G Corpas Pastor & J-P Colson on 08/05/2020, available online: https://doi.org/10.1075/ivitra.24.16tas The accepted version of the publication may differ from the final published version.

Series/Report no.

IVITRA Research in Linguistics and Literature, 24

ISBN

9789027205353

Collections

Research Institute in Information and Language Processing