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推荐算法时间动态特性研究进展 被引量：3

Research on Progress of Time-based Dynamic Recommender System
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摘要 传统推荐算法没有考虑时间效应的影响,而随着用户兴趣、产品流行度等变化,会使得推荐效果受到影响。近年来,越来越多的研究者开始关注推荐系统动态特性,时间信息对推荐系统有重要的作用,将回顾推荐系统主要算法,研究静态模型存在的问题,详细介绍近年来国内外动态推荐算法的研究进展,为后续研究提供参考。 Earlier recommender system did not take temporal effects into account.But accompanied by the change of user interests and item popularity,the performance of recommender system isn＇t so good.Therefore,in recent years more and more researchers realized that temporal information play an extremely important role in recommender systems.This paper reviews the methods of recommender system,and discusses what＇s the main problem of static model without time information.Furthermore,introduces the progress of time-based dynamic recommender system research in recent years.
作者 朱思丞 黄瑛 孙志锋
机构地区 浙江大学电气工程学院 中国人民解放军理工大学指挥信息系统学院
出处 《工业控制计算机》 2015年第8期99-100,103,共3页 Industrial Control Computer
关键词 推荐系统 协同过滤 时间效应 兴趣变化 动态特性 recommender system collaborative filtering temporal effects interests changing dynamic features
分类号 TP391.3 [自动化与计算机技术—计算机应用技术]
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参考文献16

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二级参考文献66

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共引文献285

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工业控制计算机
2015年 第8期

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