摘要
随着信息时代的不断发展,信息过载是目前互联网用户面临的一个严重问题,个性化推荐系统就是解决这一问题的重要工具。为了解国内对个性化推荐领域的研究现状与发展趋势,通过对相关文献进行收集处理并借用VOSviewer、Excel对发文量、发文期刊、发文作者、关键词进行现状分析,同时对个性化推荐系统的关键技术用户兴趣模型和推荐算法进行阐述介绍。最后指出了未来个性化推荐系统的挑战与研究重点。
With the continuous development of the information age,information overload is a serious problem faced by Internet users.The personalized recommendation system is an important tool to solve this problem.In order to understand the research status and development trend of the domestic personalized recommendation field,through the collection and processing of related documents and borrowing VOSviewer and Excel to analyze the current situation of the volume of publications,publications,authors and keywords,and at the same time,the personalized recommendation system key technology user interest models and recommendation algorithms are presented.Finally,the challenges and research priorities of the personalized recommendation system in the future are pointed out.
作者
张宇航
姚文娟
姜姗
ZHANG Yu-hang;YAO Wen-juan;JIANG Shan(School of Management Science and Engineering,Anhui University of Finance and Economics,Bengbu 233030,China)
出处
《价值工程》
2020年第2期287-292,共6页
Value Engineering
基金
2018年安徽财经大学大学生创新创业训练计划项目“大数据推动社交网络个性化推荐的发展”（201810378413）
关键词
个性化推荐
用户兴趣
推荐算法
personalized recommendation
user interest
recommendation algorithm
