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.

Saqib Alam and Nianmin Yao, “Probabilistic Neural Network and Word Embedding for Sentiment Analysis” International Journal of Advanced Computer Science and Applications(IJACSA), 9(7), 2018. http://dx.doi.org/10.14569/IJACSA.2018.090708

@article{Alam2018,
title = {Probabilistic Neural Network and Word Embedding for Sentiment Analysis},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.090708},
url = {http://dx.doi.org/10.14569/IJACSA.2018.090708},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {7},
author = {Saqib Alam and Nianmin Yao}
}