Algorithm study under big data environment of personalized recommendation based on user interest model

Abstract

Based on core problems of personalized recommendation, traditional collaborative filtering recommendation algorithm and theories of AprioriAll 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 that the accuracy and real-time of recommendation is improved through the model and algorithm under big data environment.