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Analysis and Prediction of Customers’ Reviews with Amazon Dataset on Products

  • Shitanshu JainEmail author
  • S. C. Jain
  • Santosh Vishwakarma
Conference paper
  • 41 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1077)

Abstract

The main objective of this paper is to get a deeper knowledge of the text classification methods used in text mining. This paper describes different methods and algorithms used in text mining. Various text preprocessing steps have been performed like tokenization, case folding, stemming, stopword removal, etc. The customer reviews posted in the amazon website have been used as the training set and used with various classifiers like Naive Bayes, KNN, random forest and decision tree. The performance parameter of each method is determined with standard evaluation parameters such as precision, recall, and kappa measures. The results show that K-nearest neighbor method gives the optimal performance with the same dataset.

Keywords

Text mining methods and techniques Naive Bayes KNN Decision tree Performance parameter 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Shitanshu Jain
    • 1
    Email author
  • S. C. Jain
    • 1
  • Santosh Vishwakarma
    • 2
  1. 1.Amity UniversityMadhya PradeshIndia
  2. 2.Gyan Ganga Institute of Technology and SciencesJabalpurIndia

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