Algorithm study under big data environment of personalized recommendation based on user interest model
Qingju Guo, Wentian Ji, Zhou Renyun · 2017
Based on core problems of personalized recommendation, traditional collaborative filtering recommendation algorithm and theories of Apriori All algorithm based on association rule, it is proposed to build two-dimension user interest model combining user's implicit and explicit interests and increase the threshold value of third dimension time in this paper t o realize the real-time personalized recommendation based on user interest. Through experimental evaluation, it is proved th at the accuracy and real-time of recommendation is improved through the model and algorithm under big data environment.