Movie Recommendation System Using Hybrid Filtering and Sentimental Analysis

Authors

  • Dr. M. Saravanamuthu  Assistant Professor, Department of Computer Applications, Madanapalle Institute of Technology and Science, Madanapalle, Andhra Pradesh, India
  • M. Gowthami  PG Student, Department of Computer Applications, Madanapalle Institute of Technology and Science, Madanapalle, Andhra Pradesh, India

Keywords:

Machine Learning, KNN, Natural Language Processing (NLP).

Abstract

As humans' opinions help enhance products efficiency, and since the success or the failure of a movie depends on its reviews, there is an increase in the demand and need to build a good sentiment analysis model that classifies movies ratings. In this research, tokenization is employed to transfer the input string into a word vector, stemming is utilized to extract the root of the words, feature selection is conducted to extract the essential words, and finally classification is performed to label reviews as being either positive or negative. We build this model simply by using KNN.

References

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2023-08-30

Issue

Volume 9, Issue 4, July-August-2023

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Dr. M. Saravanamuthu, M. Gowthami, " Movie Recommendation System Using Hybrid Filtering and Sentimental Analysis" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 9, Issue 4, pp.52-56, July-August-2023.