A Comprehensive Empirical Evaluation of Existing Word Embedding Approaches

arXiv:2303.07196v2 Announce Type: replace
Abstract: Vector-based word representations help countless Natural Language Processing (NLP) tasks capture the language's semantic and syntactic regularities. In this paper, we present the characteristics of existing word embedding approaches and analyze them with regard to many classification tasks. We categorize the methods into two main groups - Traditional approaches mostly use matrix factorization to produce word representations, and they are not able to capture the semantic and syntactic regularities of the language very well. On …

abstract analyze arxiv classification cs.cl cs.ne embedding evaluation language language processing natural natural language natural language processing nlp paper processing regard semantic tasks them type vector word word embedding