A Survey on Travel Package Recommendation

Computer Engineering

A recommender system's goal is to generate meaningful recommendations to a set of users for products or items that might interest them. Suggestions for different types of goods on Amazon, or movies on Netflix etc, are actual examples of recommendation system. Recommendation system’s design depends on the domain and also on the particular characteristics of the data which is available. Online travel package information for tourist is playing vital role nowadays. The travel package information which is available online enforces an increasing challenge for tourists who have to choose from a large number of available travel packages for fulfill their personalized needs. Indeed, this article explains a case study of utilizing online travel information for personalized travel package recommendation. Here, the main challenge is to tackle the unique characteristics of travel data, which differentiate travel packages from traditional items of others for recommendation purpose. For this, first examine the characteristics of the previously offered travel packages and develop a tourist-area-season topic (TAST) model. A hybrid approach is developed for travel package recommendation by taking the base of TAST model. A hybrid approach is generated according to the topic model representation so that to form lists for personalized travel package recommendation. Tourist-Relation-Area-Season-Topic (TRAST) model is used for finding out the hidden relationship between the tourists. TRAST model is used as an effective appraisal for travel group formation.

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