Research of reading content recommendation based on behavior mining
Qingcheng Li, Zhenhua Dong, Shan Lin, Jiaxin Liu · 2008
It is more and more difficult to find proper information for people in modern knowledge explosion society. Information recommendation systems can reduce information overload and provide appropriate content to targeted user. This paper proposes a new personalized recommendation technique based on mining the user’s reading behavior through 5W1H scheme. By comparing the user profile and the information representation, we can recommend the customized content in suitable time to satisfy the user’s personalized requirement. For performance evaluation, we implement the service to make experiments on real information and people. The results show that our technology and approach can acquire the user’s reading requirement, and recommend suitable information they really need.