Analysis of Italian Word Embeddings
arXiv:1707.08783v44 citations
Originality Synthesis-oriented
AI Analysis
This work provides guidance for tuning word embeddings in Italian, but it is incremental as it applies existing methods to a new language.
The paper analyzed the performance of skip-gram and continuous bag of words word embedding algorithms for Italian, identifying optimal hyperparameter configurations for specific tasks.
In this work we analyze the performances of two of the most used word embeddings algorithms, skip-gram and continuous bag of words on Italian language. These algorithms have many hyper-parameter that have to be carefully tuned in order to obtain accurate word representation in vectorial space. We provide an accurate analysis and an evaluation, showing what are the best configuration of parameters for specific tasks.