High Impact Factor : 4.396 icon | Submit Manuscript Online icon |

A Novel Approach for Travel Package Recommendation by using TAST & TRAST Model


Ashwini D. Mate , Bharati Vidyapeeth College of engineering,Belpada,C.B.D.,Navi Mumbai; Dr. D. R. Ingle, Bharati Vidyapeeth College of engineering,Belpada,C.B.D.,Navi Mumbai


tourist- area-season topic (TAST), tourist-relation-area-season topic (TRAST)


In this paper, we aim to make personalized travel package recommendations for the tourists. Thus, the users are the tourists and the items are the existing packages, and we exploit a real-world travel data set provided by a travels for building recommender systems. We develop a tourist- area-season topic (TAST) model, which can represent travel packages and tourists by different topic distributions. In the TAST model, the extraction of topics is conditioned on both the tourists and the intrinsic features (i.e., locations, travel seasons) of the landscapes. Based on this TAST model, a integrated approach is developed for personalized travel package recommendation by considering some additional factors including the seasonal behaviors of tourists, the prices of travel packages, and the cold start problem of new packages. Finally, we combine the TAST model, the TRAST model, and the integrated recommendation approach on the real-world travel package data. Experimental results show that the TAST model can effectively capture the unique characteristics of the travel data and the integrated approach which is much more effective than traditional recommendation techniques for travel package recommendation. Also, by considering tourist relationships, the TRAST model can be used as an effective assessment for travel group formation.

Other Details

Paper ID: IJSRDV5I50009
Published in: Volume : 5, Issue : 5
Publication Date: 01/08/2017
Page(s): 23-27

Article Preview

Download Article