Word Embeddings Go to Italy: A Comparison of Models and Training Datasets

Abstract

In this paper we present some preliminary results on the generation of word embeddings for the Italian language. We compare two popular word representation models, word2vec and GloVe, and train them on two datasets with different stylistic properties. We test the generated word embeddings on a word analogy test derived from the one originally proposed for… (More)

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Cite this paper

@inproceedings{Berardi2015WordEG, title={Word Embeddings Go to Italy: A Comparison of Models and Training Datasets}, author={Giacomo Berardi and Andrea Esuli and Diego Marcheggiani}, booktitle={IIR}, year={2015} }