Abstract

In the present days, Artificial Intelligence (AI) is an attractive area of research along with numerous practicable purposes and vigorous subject matters and tasks, such as, understand speech, natural language, diagnose medicine and support basic research. In this study deep learning (DL) techniques, i.e. Probabilistic Neural Network (PNN) and Word Embedding (WE) will be used for sentiment analysis. The entire proposed framework will be divided into three phases: (a) normalization, (b) word vectorization, and (c) execution of proposed model.

Details

Title
Probabilistic Neural Network and Word Embedding for Sentiment Analysis
Author
Alam, Saqib; Yao, Nianmin
Publication year
2018
Publication date
2018
Publisher
Science and Information (SAI) Organization Limited
ISSN
2158107X
e-ISSN
21565570
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2656410969
Copyright
© 2018. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.