摘要
在个性化推荐系统中,协同过滤技术是应用最成功的技术。协同过滤技术包含几种典型代表,基于用户的协同过滤、基于内容项的协同过滤、基于关联规则的协同过滤等,这些方法都有各自的优缺点和应用领域。通过对传统协同过滤算法进行分析,根据移动用户餐饮个性化的特点,引入杰卡德系数,将杰卡德系数引入到协同过滤中并对算法进行改进,最终在移动用户餐饮个性化推荐中取得了较为理想的效果。
In the personalized recommendation system,collaborative filtering technology is one of the most successful tech-nologies in application,which contains a few typical modes：collaborative filtering technologies based on the users,content items,association rules and so on,. These technologies have their own advantages,disadvantages and application fields. By the analysis of the traditional collaborative filtering algorithm,Jaccard coefficient is introduced according to the catering persona-lized characteristic of the mobile users. Jaccard coefficient is introduced into collaborative filtering to improve the filtering algo-rithm.,An ideal effect was obtained in catering personalized recommendation for mobile users.
出处
《现代电子技术》
北大核心
2015年第11期13-15,共3页
Modern Electronics Technique
基金
陕西省教育厅科学研究计划项目(14JK1307)
关键词
个性化
协同过滤
杰卡德系数
相似性
personalization
collaborative filtering
Jaccard coefficient
similarity
作者简介
朱保华（1987-），男，硕士研究生。主要研究领域为个性化服务技术与应用。
张晓滨（1970-），男，副教授，硕士生导师。主要研究领域为数据挖掘技术、个性化服务技术与应用等。
