# New word analogy corpus for exploring embeddings of Czech words

arXiv: https://arxiv.org/abs/1608.00789 · HTML: https://mlsanity.com/paper/1608.00789/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Aug 2016.

## Built on by (most cited first, 1 of 1)

- [One Size Does Not Fit All: Finding the Optimal Subword Sizes for FastText Models across Languages](https://mlsanity.com/paper/2102.02585/) (2021)

## Abstract (arXiv)

The word embedding methods have been proven to be very useful in many tasks of NLP (Natural Language Processing). Much has been investigated about word embeddings of English words and phrases, but only little attention has been dedicated to other languages. Our goal in this paper is to explore the behavior of state-of-the-art word embedding methods on Czech, the language that is characterized by very rich morphology. We introduce new corpus for word analogy task that inspects syntactic, morphosyntactic and semantic properties of Czech words and phrases. We experiment with Word2Vec and GloVe algorithms and discuss the results on this corpus. The corpus is available for the research community.