TRAVELMATE Travel Package Recommendation System

The rapid increase in travel information online brings a growing challenge for tourists who have to choose from a large number of travel packages available to meet their personal needs. It has come to the conclusion that today's aggressive tourism situation in order to increase its market and maintain control of these companies would be forced not to use data mining techniques and tools to develop, manage products and services in the tourism market. The aim of this paper is to provide and demonstrate data mining and their application in tourism. In this document we first analyze the characteristics of existing travel packages and develop a thematic model of the tourist Area Season Topic (TAST). Based on this model, we suggest cocktail approach to create lists for customized travel package recommendations. In addition, we extended the TAST model to TRAST to capture the latent relationships between tourists in each tour group.Finally, we have evaluated the TAST model, the TRAST model and the recommended cocktail access in the real world travel package data.