Research on food review system based on collaborative filtering algorithm
As people's pursuit of various delicacies is becoming more and more intense,how to recommend information about food stores that meet the needs of each user has become a new problem.This paper adopts the architecture of SpringBoot and Vue.js,which separates the front and backend,and trains a model-based collaborative filtering algorithm based on the user's review data in the catering evaluation system to predict the user's rating data,and finally recommends different stores for different users according to the level of the predicted score,so as to realize the personalized recommendation of the food review system.
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