An experimental study of sentiment classification using deep-based models with various word embedding techniques

IF 1.7 4区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Journal of Experimental & Theoretical Artificial Intelligence Pub Date : 2024-07-30 DOI:10.1080/0952813x.2024.2384568

Sajad Rezaei, Jafar Tanha, Seyedehsan Roshan, Zahra Jafari, Mahdi Molaei, Samira Mirzadoust, Mohammad Sadeghi, Amir Forsati, Tara Khoshamouz

引用次数: 0

Abstract

Nowadays, sentiment analysis is concerned with identifying and analysing text sentiment. Sentiment analysis has been used in many fields because of its applications in various domains. In the last ...

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使用基于深度的模型和各种词嵌入技术进行情感分类的实验研究

如今，情感分析主要涉及识别和分析文本情感。情感分析因其在不同领域的应用而被广泛使用。在过去的 ...

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来源期刊

Journal of Experimental & Theoretical Artificial Intelligence 工程技术-计算机：人工智能

CiteScore

6.10

自引率

4.50%

发文量

审稿时长

>12 weeks

期刊介绍： Journal of Experimental & Theoretical Artificial Intelligence (JETAI) is a world leading journal dedicated to publishing high quality, rigorously reviewed, original papers in artificial intelligence (AI) research. The journal features work in all subfields of AI research and accepts both theoretical and applied research. Topics covered include, but are not limited to, the following: • cognitive science • games • learning • knowledge representation • memory and neural system modelling • perception • problem-solving