Research on the differentiation of residents’ cultural consumption tendency and consumption recommendation system based on network inference algorithm

Abstract

In order to solve the problem of insufficient accuracy of consumer recommendation systems, the study proposes to design a new network inference algorithm with bias based on the traditional network inference algorithm. Then the performance of this algorithm is verified by means of comparison experiments with NBI, SNBI and HNBI algorithms. The results show that the new network inference algorithm has an accuracy rate of 24.5%, which is better than the traditional network inference algorithm. In terms of the constituted system performance test, the recommendation hit rate of the novel network inference algorithm increases by 13.97%, which is better than NBI, SNBI, and HNBI. the experimental results indicate that the novel network inference algorithm with bias can improve the performance of the consumer recommendation system, which provides a new idea for the performance improvement of the consumer recommendation system.