Opinion Mining Approach to Improve Hotel Booking Process

Abstract

Customer Opinions play a very crucial role in daily life. When we have to take a decision, others opinion also considered. The e-commerce field has developed to the point that more and more hotel companies provide online booking services to travellers as an integral part of their business model. Increasing numbers of hotel companies now provide such services as an integral part of their business model and their guests’ experiences with their hotel. Some third-party services allow customers to add comments on each hotel at the affiliated website. The proposed tool features at hotel websites are based on fixed properties, allowing companies to take advantage of the huge number of available customer reviews to provide relevant information to consumers considering new services. In this thesis we are going to see how Sentiment analysis tool is working used for mining reviews from online reviews those are posted by customers. How Apriori frequent item set mining algorithm can be used for find associate hotel features. Our main theme is to create a system for analyzing opinions which implies judgment of different consumer products. This research should improve online hotel booking by building a customized tool that utilizes available customer reviews at the Trip Advisor website. In this thesis we are going to see how.