科研成果详情

题名Censorious Young: Knowledge Discovery from High-throughput Movie Rating Data with LME4
作者
发表日期2019-05-10
会议名称4th IEEE International Conference on Big Data Analytics (ICBDA)
会议录名称2019 4th IEEE International Conference on Big Data Analytics, ICBDA 2019
页码32-36
会议日期MAR 15-18, 2019
会议地点Suzhou
会议举办国PEOPLES R CHINA
摘要

Quantitative analysis of high throughput movie rating data provides supports for one general social behavior: the young are usually more censorious than senior people when rating/evaluating the same thing. Millions of movie rating data with users' categorical age information are analyzed by the linear mixed model with the lme4 R package. When the age factor is viewed as fixed effects, the rating scores for movies are positively related to age. In general the young people are tends to give lower score than senior people. Such a social behavior phenomenon should be carefully examined in a recommendation system and in data collection.

关键词Knowledge discovery in databases(KDD) linear-mixed effects model(LMM) lme4 software recommender system (RS)
DOI10.1109/ICBDA.2019.8713193
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收录类别CPCI-S
语种英语English
WOS研究方向Computer Science
WOS类目Computer Science ; Information Systems ; Computer Science ; Software EngineeringComputer Science, Theory & Methods
WOS记录号WOS:000469958800007
Scopus入藏号2-s2.0-85066604329
引用统计
被引频次:3[WOS]   [WOS记录]     [WOS相关记录]
文献类型会议论文
条目标识符https://repository.uic.edu.cn/handle/39GCC9TT/11505
专题个人在本单位外知识产出
作者单位
Department of Mathematics,Xi'An Jiaotong-Liverpool University,China
推荐引用方式
GB/T 7714
Chen, Zhiyi,Zhu, Shengxin,Niu, Qianget al. Censorious Young: Knowledge Discovery from High-throughput Movie Rating Data with LME4[C], 2019: 32-36.
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