A user-location vector based approach for personalised tourism and travel recommendation

Social networking websites allows us to understand the user's interest and behavior pattern on various Travel and Tourism services, especially travel attractions and point of interest, which can be exploited to recommend personalized list of places to users. The major challenge faced by Travel and Tourism recommendation System is to understand the implicit relationships that exist between the user and the point of interest. In this work we have introduced a novel approach to represent and identify the implicit relationship between user and point of interest using a vector called user-location vector. Experimental and evaluation result shows that this recommender system, using the user-location vector, produces 65%-100% effectiveness compared to the existing system in both prediction and ranking.