An new method to collaborative filtering recommendation based on DBN and HMM

MATEC Web of Conferences

Guo Zheng Xin¹  Zhao Yong Mei²  Wan Hai Rong³ 

[1] Department of Civil Engineering, Hunan University;Department of Electric and Science, College of Science, Air Force Engineering University;Department of Urban and Regional Planning, College of Urban and Environmental Sciences, Peking University;

关键词: hidden markov model(HMM);    dynamic bayes network(DBN);    collaborative filtering recommendation;   

DOI  :  10.1051/matecconf/20164401091

来源: DOAJ

【 摘 要 】

The main problems of collaborative filtering are initial rating, data sparsity and recommendation in time. A recommendation approach based on HMM model, which creates nearest neighbour set by simulating the user behaviours of web browsing, is a good way to solve the above problems. However, the HMM or model parameters constantly vary with customer's changing preference. When there is a new type of data to join, the HMM can only be discovered by relearn, which will affect real time of recommendation. Therefore a recommendation approach based on DBN and HMM is proposed. The approach will improve real time recommendation, and experiments shows that it has high recommendation quality.

【 授权许可】

Unknown