Probabilistic Neural Network and Word Embedding for Sentiment Analysis

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...

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Published inInternational journal of advanced computer science & applications Vol. 9; no. 7
Main Authors Alam, Saqib, Yao, Nianmin
Format Journal Article
LanguageEnglish
Published West Yorkshire Science and Information (SAI) Organization Limited 2018
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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.
AbstractList 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.
Author Alam, Saqib
Yao, Nianmin
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SubjectTerms Artificial intelligence
Data mining
Embedding
Neural networks
Sentiment analysis
Words (language)
Title Probabilistic Neural Network and Word Embedding for Sentiment Analysis
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