ROLE OF ARTIFICIAL NEURAL NETWORK IN OPINION CLASSIFICATION

Authors

  • Dr. Helen Josephine V L Associate Professor, Department of Computer Applications, CMR Institute of Technology, Bengaluru Author
  • Gomathi Thiyagarajan Assistant Professor, Department of Computer Applications, CMR Institute of Technology, Bengaluru Author
  • Dr. V. S. Anita Sofia Associates Professor, Department of Computer Technology, Sri Krishna Arts and Science College, Coimbatore Author

DOI:

https://doi.org/10.61841/peh8p689

Keywords:

Classification, Machine Learning, Neural Network, Opinion Mining

Abstract

In the present world, internet users are expanding rapidly, and consumers are more involved in searching for and selecting the best product. E-commerce organizations also spend a lot of time, effort, and cost to investigate the comments and feedback about their products. This scrutiny would assist the corporations to enhance their services and products at low cost, which in turn would facilitate them to extend and flourish in the industry. Extracting knowledge from vast unstructured data, which is in the form of customer reviews, finds it very difficult to analyze and evaluate. This research paper analyzes the role of neural networks in opinion mining classification and proposes a gain ratio feedforward neural network (GR_FFNN) algorithm to improve classification accuracy. This paper also compares the GR_FFNN algorithm with the existing neural network classifier. 

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Published

30.04.2020

Issue

Vol. 24 No. 2 (2020): 24 (2) 2020

Section

Articles

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How to Cite

Josephine V L, H., Thiyagarajan, G., & Anita Sofia, V. S. (2020). ROLE OF ARTIFICIAL NEURAL NETWORK IN OPINION CLASSIFICATION. International Journal of Psychosocial Rehabilitation, 24(2), 4407-4416. https://doi.org/10.61841/peh8p689