Personalized Trip Information for E-Tourism Recommendation System Based on Bayes Theorem

摘要

This paper presents the personalized recommendation system for e-tourism by using statistic technique base on Bayes Theorem to analyze user behaviors and recommend trips to specific users. The system is evaluated by using Recall, Precision and F-measure. Results demonstrate that it is possible to develop Personalization Recommendation System. Past and recent information of customer's behaviors are used for recommending products and services best fit to relevant customers in the e-Tourism.