rohitg57 / travel-review-segmentation Goto Github PK

Abstract:

Understanding the tastes of each user and the characteristics of each product is necessary to predict how a user will respond to a new product. This latent user and product dimensions can be discovered with the help of user feedback. A numeric rating and its accompanying text review is the most widely available form of user feedback. A measure which encapsulates the contents of such reviews is often necessary as they have been found to significantly influence the shopping behaviour of users. A fine-grained form of such measure that could act as perfect feedback about the product is a star rating. The review rating prediction tries to predict a rating corresponding to the given review.

Problem Statement:

Given the google rating data, use a hierarchical clustering algorithm to cluster reviews.

Dataset Information:

This data set is populated by capturing user ratings from Google reviews. Reviews on attractions from 24 categories across Europe are considered. Google user rating ranges from 1 to 5 and the average user rating per category is calculated.