Mining user daily behavior patterns from access logs of massive software and websites
文献类型：会议论文
| 作者 | Wei, Zhao (1) ; Jie, Liu (2) ; Dan, Ye (2) ; Jun, Wei (2) |
| 出版日期 | 2013 |
| 会议名称 | 5th Asia-Pacific Symposium on Internetware, Internetware 2013 |
| 会议日期 | October 23, 2013 - October 24, 2013 |
| 会议地点 | Changsha, China |
| 中文摘要 | Everyone has a characteristic pattern of daily activities. This study applies cluster analysis to identify a computer user's daily behavior patterns based on 1000 China users' 4-weeks software and web usage. Clustering models are built for 4 different behavior definition methods with different time period divisions and feature measurement selections. With these patterns, we build classification models to predict new users' daily behavior pattern with their half day activity logs. For example, if we know one user use computer for entertainment in the morning, we can predict his behavior in the afternoon and evening. The prediction model can be used to recommend suitable items to users according to their current behavior status. Our method can get 92.5% prediction correctness for the best. |
| 英文摘要 | Everyone has a characteristic pattern of daily activities. This study applies cluster analysis to identify a computer user's daily behavior patterns based on 1000 China users' 4-weeks software and web usage. Clustering models are built for 4 different behavior definition methods with different time period divisions and feature measurement selections. With these patterns, we build classification models to predict new users' daily behavior pattern with their half day activity logs. For example, if we know one user use computer for entertainment in the morning, we can predict his behavior in the afternoon and evening. The prediction model can be used to recommend suitable items to users according to their current behavior status. Our method can get 92.5% prediction correctness for the best. |
| 收录类别 | EI |
| 会议录出版地 | Association for Computing Machinery, General Post Office, P.O. Box 30777, NY 10087-0777, United States |
| 语种 | 英语 |
| ISBN号 | 9781450323697 |
| 源URL | [http://ir.iscas.ac.cn/handle/311060/16676]  |
| 专题 | 软件研究所_软件所图书馆_会议论文 |
| 推荐引用方式 GB/T 7714 | Wei, Zhao ,Jie, Liu ,Dan, Ye ,et al. Mining user daily behavior patterns from access logs of massive software and websites[C]. 见:5th Asia-Pacific Symposium on Internetware, Internetware 2013. Changsha, China. October 23, 2013 - October 24, 2013. |
入库方式： OAI收割
来源：软件研究所
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