Naïve Bayes Algorithm for Large Scale Text Classification
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1. Department of Information and Communication Technology, Faculty of Technology, Rajarata University of Sri Lanka, Mihintale 50300, Sri Lanka;
2. Department of Computer Science and Informatics, Faculty of Applied Sciences, Uva Wellassa University of Sri Lanka, Badulla 90000, Sri Lanka

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    Abstract:

    This paper proposed an improved Naïve Bayes Classifier for sentimental analysis from a large-scale dataset such as in YouTube. YouTube contains large unstructured and unorganized comments and reactions, which carry important in-formation. Organizing large amounts of data and extracting useful information is a challenging task. The extracted information can be considered as new knowledge and can be used for decision-making. We extract comments from YouTube on videos and categorized them in domain-specific, and then apply the Naïve Bayes classifier with improved techniques. Our method provided a decent 80% accuracy in classifying those comments. This experiment shows that the proposed method provides excellent adaptability for large-scale text classification.

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Pirunthavi SIVAKUMAR, Jayalath EKANAYAKE.[J]. Instrumentation,2021,8(4):55-62

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  • Received:
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  • Online: May 26,2022
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