Hotel Recommendation System using Hadoop and Sentiment Analysis

"Sentiment Analysis Based Keyword Aware Service Recommendation for Big Data" Traditional recommender systems lack to give personalized recommendation to the end user. They lack in providing scalability and efficiency. Rating list and recommendation provided was almost same. So, in this paper a hotel recommendation system using hadoop framework is proposed. Hadoop mainly works in the area where big data appears. This big data is hard to capture and analyze. A review based service recommendation method is proposed to tackle this problem. This method is based on a user based collaborative filtering algorithm. Users having similar tastes are captured with the help of keywords they enter. Then Sentiment Analysis is applied on passive users reviews and a score is calculated. Top-k services are recommended to the end user. Experimental analysis shows that this method works more efficiently than traditional available methods.