Research on personalized recommendation model for mobile advertising
Qiwei Gu, Peng Guo · 2012
Aimed at enhancing the accuracy of the personalized recommendation for mobile advertising, overcoming the shortcomings of the traditional similarity calculation and collaborative filtering recommendation techniques, the cloud model calculation method improved the strict item or project matching problem in traditional similarity calculation, resolved extreme sparse data problem. And a mixed recommendation model is established based on mobile advertisement, content recommendation and linear combination of collaborative filtering recommendation. Experiments prove that the new method has obviously smaller MAE and higher quality in recommendation system.