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 extensive analysis and an evaluation, showing what are the best configuration of parameters for specific analogy tasks.
|Titolo:||Analysis of Italian Word Embeddings|
|Data di pubblicazione:||2017|
|Appare nelle tipologie:||4.1 Articolo in Atti di convegno|