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The Use of Supervised Text Classification Techniques: A Comprehensive Study

Publication Type : Conference Paper

Publisher : IEEE

Source : 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE)

Url : https://doi.org/10.1109/icacite53722.2022.9823416

Campus : Faridabad

School : School of Artificial Intelligence

Year : 2022

Abstract : Every second in social networking, a massive amount of feedback, comments, and posts are made, resulting in a massive increase in the social database. It's now necessary to go through enormous amounts of data to figure out how people feel about a certain company or product. Most online evaluations are published in English, but as technology and people's understanding improve, Hindi-language material is becoming more prevalent on the internet. In addition, knowing people's views about a particular item is an important component of Indian language sentiment analysis; we consider all of their thoughts to be equally valid. To boost the accuracy of our categorization, we used the Hindi language repository for general news stories from a number of news sources. Text classification accuracy was investigated using Naive Bayes and other machine learning classification techniques, as well as Random Forest, Support Vector Machines, and Logistic Regression approaches.

Cite this Research Publication : Vijay Kumar Soni, Durgesh Srivastava, The Use of Supervised Text Classification Techniques: A Comprehensive Study, 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), IEEE, 2022, https://doi.org/10.1109/icacite53722.2022.9823416

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