A Precisely Xtreme-Multi Channel Hybrid Approach for Roman Urdu Sentiment Analysis

A Precisely Xtreme-Multi Channel Hybrid Approach for Roman Urdu Sentiment Analysis

In order to accelerate the performance of various Natural Language Processing tasks for Roman Urdu, this article for the very first time provides 3 neural word embeddings prepared using most widely used approaches namely Word2vec, FastText, and Glove. The integrity of generated neural word embedding...

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Bibliographic Details
Main Authors: Faiza Mehmood, Muhammad Usman Ghani, Muhammad Ali Ibrahim, Rehab Shahzadi, Waqar Mahmood, Muhammad Nabeel Asim
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Fast-text
glove
pretrain word embeddings for roman Urdu
roman Urdu sentiment analysis
Word2Vec
Online Access:https://ieeexplore.ieee.org/document/9223633/

Internet

https://ieeexplore.ieee.org/document/9223633/

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