Personalized Recommendation of Mobile Tourism: a Multidimensional User Model

With rapid advances in e-business and mobile technology, the personalized recommendation of mobile tourism becomes a critical issue for both researchers and practitioners. The big data, problems of new users and similar recommendations remain barriers for mobile tourism. Through a large dataset gathered by questionnaires, this paper develops a novel multidimensional user model from the perspective of context. The dimensions of our model include several factors: historical behaviour, context and demographic feature of users. To make a better understanding of the model, a case study was adopted. Besides, an experiment is also conducted to evaluate the performance of the proposed model. As a conclusion, limitations and future researches are discussed.