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Enhance Rating Algorithm for Restaurants

  • Jeshreen BalrajEmail author
  • Cassim Farook
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 70)

Abstract

More and more people make their purchase decisions by referring to reviews and ratings provided in online platforms. Visitors to restaurants use online reviews on a larger scale compared with the users of other industries. However, for these visitors, evaluating numerous reviews is a hassle and time consuming as it involves a process of reading through all the reviews, identifying the date of review posting, understanding the reviewer’s credibility and identifying the rating of the reviewer and the restaurant before making the decision. This research proposes an enhanced rating algorithm which will calculate an overall rating. Apart from the standard point rating the solution will include the aspect, sentiment, time factor and user credibility of a review. The enhanced algorithm uses Natural Language Processing and Sentiment analysis used with machine learning to identify the thoughts of the user regarding the restaurants. The algorithm is tested with a web-based solution that gives an overall idea of the current performance of a particular restaurant utilizing reviews of those restaurants. The new algorithm gives a much credible rating than the conventional rating systems.

Keywords

Natural language processing Sentiment analysis Algorithm Machine learning 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Informatics Institute of TechnologyColomboSri Lanka

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