摘要
大数据时代带来的信息过载问题加速了个性化推荐系统发展,而将仿真实验系统与推荐算法或模型结合是推动个性化推荐研究进展的有效方式。仿真系统可以有效检验推荐系统的性能指标是否优良,帮助学者更好地确定未来研究方向。从个性化推荐技术、应用以及仿真三方面进行文献梳理,重点总结目前个性化推荐仿真研究现状,并在最后针对推荐仿真研究不足部分提出未来研究方向,可为个性化推荐及仿真领域提供研究借鉴。
The information overload problem brought about by the Internet era accelerates the development of personalized recommending systems,and the combination of simulation experiment systems and recommending algorithms or models is an effective way to promote the research progress of personalized recommendation.Simulation systems can effectively test whether the performance indexes of the recommendation systems is good or not,and help scholars to better determine the future research direction.Combs the literature from three aspects of personalized recommending technology,application and simulation,focusing on the current research status of personalized recommending simulation,and finally puts forward the future research direction in view of the shortcomings of recommending simulation research,it can provide research reference for the field of marketing.
作者
龚映梅
侯玉寒
杨红娟
GONG Ying-mei;HOU Yu-han;YANG Hong-juan(Faculty of Management and Economics,Kunming University of Science and Technology,Kunming 650093,China)
出处
《科技和产业》
2021年第5期72-80,共9页
Science Technology and Industry
基金
教育部人文社会科学研究规划基金项目(15XJA630004)
2019年云南省哲学社会科学研究基地项目(JD2019YB08)。
关键词
个性化推荐
技术及应用
仿真
personalized recommendation
technology and application
simulation
