Reviews Sentiment analysis for collaborative recommender system

https://doi.org/10.24017/science.2017.3.22

Abstract views: 1531 / PDF downloads: 1505

Authors

  • Alia Karim Abdul Hassan Computer science Dept, University Of Technology Baghdad, Iraq
  • Ahmed Bahaa Aldeen Abdulwahhab Informatics Dept, Middle Technical University Baghdad, Iraq

Abstract

recommender system nowadays is used to deliver services and information to users. A recommender system is suffering from problems of data sparsity and cold start because of insufficient user rating or absence of data about users or items. This research proposed a sentiment analysis system work on user reviews as an additional source of information to tackle data sparsity problems. Sentiment analysis system implemented using NLP techniques with machine learning to predict user rating form his review; this model is evaluated using Yelp restaurant data set, IMDB reviews data set, and Arabic qaym.com restaurant reviews data set under various classification model, the system was efficient in predicting rating from reviews.

Keywords:

recommender systems, sentiment analysis, opinion mining, natural language processing, text classification.

References

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Published

27-08-2017

Issue

Section

Pure and Applied Science

How to Cite

[1]
A. K. Abdul Hassan and A. B. A. Abdulwahhab, “Reviews Sentiment analysis for collaborative recommender system”, KJAR, vol. 2, no. 3, pp. 87–91, Aug. 2017, doi: 10.24017/science.2017.3.22.