Item Based Collaborative Filtering Tourism Recommender System Using Apache Mahout

Abstract

Recommender systems are one of the most widespread and well-known uses of big data. With the advent of big data technologies, the travel and tourism industry were able to collect a wealth of visitor data, such as browsing history, past reservations, and feedback information, and send it to recommendation engines to provide pertinent and helpful recommendations in real time. In this paper, Hadoop and Apache Mahout are used to create an item-based collaborative filtering tourism recommender system based on past visitors' preferences in the area of Daraâ-Tafilalet; which is a crucial region in improving tourism in Morocco.