摘要
随着移动互联网技术的迅猛发展,人们更喜欢通过手机等移动设备在社交产品上分享自己的行为足迹或者对商品服务的评价。大多数的互联网产品利用用户的用户的兴趣点等行为信息为依据为用户推荐下一个潜在偏好的兴趣点。本文显示介绍典型的兴趣点推荐算法以及相关优缺点。针对这些算法考虑单一属性的问题分析基于兴趣点的多维度推荐研究。
with the rapid development of mobile Internet technology, people prefer to share their behavior footprints or evaluation of goods and services on social products through mobile devices such as mobile phones. Most Internet products use users′ behavior information such as interest points to recommend the next potential interest point for users. This paper shows the typical algorithm of interest point recommendation and its advantages and disadvantages. In view of these algorithms considering a single attribute, this paper analyzes multi-dimensional recommendation research Based on interest points.
作者
田春波
TIAN Chun-bo(School of Computer Science,Southwest Petroleum University,Chengdu 610500,Sichuan)
出处
《电脑知识与技术》
2020年第4期171-172,共2页
Computer Knowledge and Technology
关键词
兴趣点
多维度推荐
社交网络
用户偏好
个性化推荐
interest points
multi-dimensional recommendation
social network
user preferences
personalized recommendation
