TY - JOUR
TI - Word Embeddings for Morphologically Complex Languages
AU - Jurdziński, Grzegorz
TI - Word Embeddings for Morphologically Complex Languages
AB - 
	Recent methods for learning word embeddings, like GloVe or Word2-Vec, succeeded in spatial representation of semantic and syntactic relations. We extend GloVe by introducing separate vectors for base form and grammatical form of a word, using morphosyntactic dictionary for this. This allows vectors to capture properties of words better. We also present model results for word analogy test and introduce a new test based on WordNet.
VL - 2016
IS - Volume 25
PY - 2017
SN - 1732-3916
C1 - 2083-8476
SP - 127
EP - 138
DO - 10.4467/20838476SI.16.010.6191
UR - https://ejournals.eu/en/journal/schedae-informaticae/article/word-embeddings-for-morphologically-complex-languages
KW - machine learning
KW - word embeddings
KW - natural language processing
KW - morphology 1. Introduction