Research of personalized news recommendation system based on hybrid collaborative filtering algorithm
- Resource Type
- Conference
- Authors
- Shan Liu; Yao Dong; Jianping Chai
- Source
- 2016 2nd IEEE International Conference on Computer and Communications (ICCC) Computer and Communications (ICCC), 2016 2nd IEEE International Conference on. :865-869 Oct, 2016
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Filtering algorithms
Information filters
Correlation coefficient
Fluctuations
Springs
personalized recommendation
collaborative filtering
hybrid recommendation algorithm
- Language
This paper introduced the personalized recommendation technology to the news system. Especially, in order to meet the demand of the users' personality and ease the problem of data sparse, the research work proposed the hybrid collaborative filtering algorithm based on news recommendation. By improving correlation coefficient formula via adding news hot parameter when calculating the similarity of users, the hybrid recommendation algorithm is used to forecast users' ratings to make user-rating matrix to non-zero values. Experimental results illustrated that the hybrid recommendation algorithm can effectively increase the accuracy and stability of recommendation so as to achieve better recommendation results.