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发表状态已发表Published
题名Knowledge Discovery and Recommendation with Linear Mixed Model
作者
发表日期2020
发表期刊IEEE Access
卷号8页码:38304-38317
摘要

We give a concise tutorial on knowledge discovery with linear mixed model in movie recommendation. The versatility of mixed effects model is well explained. Commonly used methods for parameter estimation, confidence interval estimate and evaluation criteria for model selection are briefly reviewed. Mixed effects models produce sound inference based on a series of rigorous analysis. In particular, we analyze millions of movie rating data with LME4 R package and find solid evidences for a general social behavior: the young tend to be more censorious than senior people when evaluating the same object. Such a social behavior phenomenon can be used in recommender systems and business data analysis.

关键词Knowledge discovery in database (KDD) linear mixed-effects model (LMM) R software recommender system (RS)
DOI10.1109/ACCESS.2020.2973170
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语种英语English
WOS研究方向Computer Science ; Engineering ; Telecommunications
WOS类目Computer Science ; Information Systems ; Engineering ; Electrical & Electronic ; Telecommunications
WOS记录号WOS:000525545900069
Scopus入藏号2-s2.0-85081643635
引用统计
被引频次:13[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符https://repository.uic.edu.cn/handle/39GCC9TT/11504
专题个人在本单位外知识产出
通讯作者Zhu, Shengxin
作者单位
1.Department of Mathematical Science,Xi'an Jiaotong-Liverpool University,Suzhou,215123,China
2.Department of Statistics,Columbia University,New York,10025,United States
3.Laboratory for Intelligent Computing and FinTech,Xi an Jiaotong-Liverpool University,Suzhou,215123,China
推荐引用方式
GB/T 7714
Chen, Zhiyi,Zhu, Shengxin,Niu, Qianget al. Knowledge Discovery and Recommendation with Linear Mixed Model[J]. IEEE Access, 2020, 8: 38304-38317.
APA Chen, Zhiyi, Zhu, Shengxin, Niu, Qiang, & Zuo, Tianyu. (2020). Knowledge Discovery and Recommendation with Linear Mixed Model. IEEE Access, 8, 38304-38317.
MLA Chen, Zhiyi,et al."Knowledge Discovery and Recommendation with Linear Mixed Model". IEEE Access 8(2020): 38304-38317.
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