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IMDB Movie Reviews Sentiment Classification Using Deep Learning

EasyChair Preprint no. 7529

4 pagesDate: March 11, 2022


Abstract- Sentiment analysis is the most commonly used method for predicting user evaluations. Various machine-learning approaches have been used to make accurate predictions regarding the data. Long-term reliance and maximum pooling are not taken into account by these classifiers. In this research, we use Deep Learning technologies to classify reviews to enhance predictions utilizing these features. In this work with the Convolution Neural Network and the Long Short Term Memory Recurrent Neural Network to get higher accuracy with less loss and less time. The performance of six machine-learning algorithms in terms of sentiment analysis in the IMDB review dataset was tested in this research. One of these algorithms is based on neural networks, whereas the others are not. For sentiment analysis in IMDB, Binary classification it has been employed.

Keyphrases: KNN algorithm, Movie Reviews, Natural Language Toolkit, Sentiment Analysis

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Ravi Kumar and Angeline Benitta},
  title = {IMDB Movie Reviews Sentiment Classification Using Deep Learning},
  howpublished = {EasyChair Preprint no. 7529},

  year = {EasyChair, 2022}}
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