Abstract:
In order to predict how a user will respond to a product, we mustuncover the tastes of
the user and the properties of the product. Forexample, in order to predict whether a
user will enjoy a food or not it depends on theuser‟s level of interest in which type of
foods user likes most. User feedback is required todiscover these dimensions, which
comes in the form of ratings andreviews. In this thesis, we aim to find a correlation
between user reviews and star ratings. However, traditional methods discard review
text, whichmakes these latent factors difficult to interpret.In this thesis, Firstly, our
approach is to analyze a text review according to the texts and find the sentiment of
the user review whether it is a positive review or negative review. Secondly, after
getting the sentimental analysis,finding the correlation between the sentimental
analysis and user star ratings. our approachmore accurately predicts sentiments by
analysing the informationpresent in review text. Our discovered methodology can be
used to identify the useful and representative reviews.
