WITHDRAWN: Word Embedding Generation for Urdu Language using Word2vec model

Abstract

Abstract Word embedding generation is the task of distributed representation of words on vector space. The word embeddings captures both the syntactic and semantic information to perform natural language processing tasks. The word embeddings has attained considerable attention from last few years giving their inherent applicability to Natural Language Processing like part of speech tagging, sentiment analyzing or dependency parsing etc. despite recent advancement in word embedding mappings, very little research has devoted for Urdu word embeddings where word with similar meaning will align to similar vector space and different far apart. In this research paper Word2vec model has been used for Urdu word embedding generation. The model will help to make the dense word vector representation of Urdu words which could be used for pre-trained word vectors. The results showed the proposed method can be used to improve conventional word embedding methods.