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Item-Based Collaborative Filtering Using Sentiment Analysis of User Reviews

  • Abhishek DubeyEmail author
  • Ayush Gupta
  • Nitish Raturi
  • Pranshu Saxena
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 899)

Abstract

Traditional Collaborative filtering algorithm works by using only the past experience of a user. To overcome the limitations of the traditional collaborative algorithm, an item based collaborative filtering system was introduced. In this paper, an improved recommender system is proposed. A dictionary of sentiment scores is created. These sentiment scores are calculated by finding the probability of the reviews to be positive. This sentiment score is used by an item based collaborative filtering system to improve the recommendations and filter out items with overall negative user opinion. The performance of the proposed system is compared with previous work done in this field.

Keywords

Collaborative filtering Item based Logistic regression Recommender systems Sentiment analysis 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Abhishek Dubey
    • 1
    Email author
  • Ayush Gupta
    • 1
  • Nitish Raturi
    • 1
  • Pranshu Saxena
    • 1
  1. 1.Department of Computer Science and EngineeringInderprastha Engineering CollegeGhaziabadIndia

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