Integrated mobile content recommendation: A comparison study
Worapat Paireekreng, Kok Wai Wong, Chun Che Fung · Murdoch Research Repository (Murdoch University) · 2012
A recommendation system can be used to help mobile device users for content filtering. However, there are problems related to sparsity of information from a first-time user. The problem is also regarding to initial rating of the content in an early stage of the system. Therefore, mobile content filtering is necessary for user to obtain personalised content delivery. This paper proposes the integrated mobile content recommendation method by combining classification and association rule techniques to establish model for new users and first rater on mobile content. The model also enhances the recommendation system in an early stage by recommending relevant items. The experiment has shown that the integrated method can perform better than the other compared methods. This can address the problem of sparsity for mobile content recommendation systems.