Abstract:
More and more people, now-a-days, make their purchase decision by referring to
reviews and ratings provided in the online platform. It is evident that the visitors to
restaurants use this facility in a larger scale compared with the users of other industries.
However, evaluating the information so gathered, is a hazel and time consuming as it
involves a process of reading through all the reviews, identifying the date of review
posting, and understanding the reviewer’s credibility before making the decision. As
a solution to this problem, the research proposes an enhanced rating algorithm which
will take into account the following to calculate an overall rating which are aspect,
sentiment, time factor and user credibility of the review. This enhanced algorithm uses
Natural Language Processing and Sentiment analysis to identify the thoughts of the
user regarding the restaurants. This will be a web-based solution that gives an overall
idea of the current performance of a particular restaurant that will guide the users to
choose a restaurant based on the overall rating with minimum hazel and time.
