Abstract
Word embedding, where words are represented as vectors in a continuous space, has recently attracted much attention in natural language processing tasks due to their ability to capture semantic and syntactic relations between words from a huge amount of text. In this work, we will focus on how word embedding can be used in Arabic word sense disambiguation (WSD).
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CITATION STYLE
Laatar, R., Aloulou, C., & Belghuith, L. H. (2018). Word2vec for arabic word sense disambiguation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10859 LNCS, pp. 308–311). Springer Verlag. https://doi.org/10.1007/978-3-319-91947-8_32
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