现代计算机2024,Vol.30Issue(22) :217-220,225.DOI:10.3969/j.issn.1007-1423.2024.22.040

基于协同过滤算法的美食点评系统研究

Research on food review system based on collaborative filtering algorithm

张晴 史率 袁宝华
现代计算机2024,Vol.30Issue(22) :217-220,225.DOI:10.3969/j.issn.1007-1423.2024.22.040

基于协同过滤算法的美食点评系统研究

Research on food review system based on collaborative filtering algorithm

张晴 1史率 2袁宝华2
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作者信息

  • 1. 南京理工大学泰州科技学院,泰州 225300
  • 2. 常州大学计算机与人工智能学院,常州 213164
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摘要

随着人们对于各种美食的追求越发强烈,如何为每个用户推荐满足其喜好的美食店家的信息成为了新的难题.采用SpringBoot与Vue.js,以前后端分离的架构,以餐饮评价系统中用户的评论数据为基础,训练基于模型的协同过滤算法,对用户的评分数据进行预测,最终根据预测评分的高低,针对不同的用户推荐不同的店铺,从而实现个性化推荐的美食点评系统.

Abstract

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.

关键词

协同过滤/美食点评/个性化推荐

Key words

collaborative filtering/food review/personalized recommendations

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出版年

2024
现代计算机
中大控股

现代计算机

影响因子:0.292
ISSN:1007-1423
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