Customized Travel Recommendation System using Big Data Analytics

Abstract

Traveling is a most important part of people lives. Travel based recommendation and journey scheduling are challenging tasks because of various interest favorites and trip limitations such as restriction of time, source and destination points for traveler’s. The travel recommendation are used to extract a large amount of information from the social media. The existing work of travel recommendation has focused on personalized recommendation. Unlike most existing travel recommendation , our perspective is not only personalized to traveler interest but also gives the hotel recommendation for the visitors. The top K query algorithm is suggested for the hotels recommendation, also provides an optimized path in an efficient way. Hence, this method addresses the customized travel recommendation problem based on travel user and similar city forecasting. The top ranked routes are optimized and gives an efficient route to the travelers. Our work provides an efficient route prediction compared with the existing system.