Distributional and Knowledge-Based Approaches for Computing Portuguese Word Similarity†
AbstractIdentifying similar and related words is not only key in natural language understanding but also a suitable task for assessing the quality of computational resources that organise words and meanings of a language, compiled by different means. This paper, which aims to be a reference for those interested in computing word similarity in Portuguese, presents several approaches for this task and is motivated by the recent availability of state-of-the-art distributional models of Portuguese words, which add to several lexical knowledge bases (LKBs) for this language, available for a longer time. The previous resources were exploited to answer word similarity tests, which also became recently available for Portuguese. We conclude that there are several valid approaches for this task, but not one that outperforms all the others in every single test. Distributional models seem to capture relatedness better, while LKBs are better suited for computing genuine similarity, but, in general, better results are obtained when knowledge from different sources is combined. View Full-Text
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Gonçalo Oliveira, H. Distributional and Knowledge-Based Approaches for Computing Portuguese Word Similarity. Information 2018, 9, 35.
Gonçalo Oliveira H. Distributional and Knowledge-Based Approaches for Computing Portuguese Word Similarity. Information. 2018; 9(2):35.Chicago/Turabian Style
Gonçalo Oliveira, Hugo. 2018. "Distributional and Knowledge-Based Approaches for Computing Portuguese Word Similarity." Information 9, no. 2: 35.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.