A cloud-based intelligent computing system for contextual exploration on personal sleep-tracking data using association rule mining
A cloud-based intelligent computing system for contextual exploration on personal sleep-tracking data using association rule mining
复制标题
基于云的智能计算系统，使用关联规则挖掘对个人睡眠跟踪数据进行上下文探索
DOI：
10.1007/978-3-319-30447-2_7
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
Takuichi Nishimura
中科院分区：
文献类型：
--
作者：
Zilu Liang;Bernd Ploderer;Mario Alberto Chapa Martell;Takuichi Nishimura
随着可穿戴和移动计算技术的发展，越来越多的人开始使用睡眠跟踪工具来收集个人每天的睡眠数据，目的是了解和改善自己的睡眠。虽然睡眠质量受到一个人的生活方式环境中的许多因素的影响，比如锻炼、饮食和走路的步数，但现有的工具只是在仪表板上可视化睡眠数据本身，而不是结合环境因素分析这些数据。因此，许多人发现很难理解他们的睡眠数据。在本文中，我们提出了一个名为SleepExplorer的基于云的智能计算系统，该系统结合了睡眠领域知识和关联规则挖掘，可以根据上下文因素对个人睡眠数据进行自动分析。实验表明，相同的环境因素可以在不同的人的睡眠中发挥不同的作用，而SleepExplorer可以帮助用户发现与他们个人睡眠最相关的因素。
With the development of wearable and mobile computing technology, more and more people start using sleep-tracking tools to collect personal sleep data on a daily basis aiming at understanding and improving their sleep. While sleep quality is influenced by many factors in a person’s lifestyle context, such as exercise, diet and steps walked, existing tools simply visualize sleep data per se on a dashboard rather than analyse those data in combination with contextual factors. Hence many people find it difficult to make sense of their sleep data. In this paper, we present a cloud-based intelligent computing system named SleepExplorer that incorporates sleep domain knowledge and association rule mining for automated analysis on personal sleep data in light of contextual factors. Experiments show that the same contextual factors can play a distinct role in sleep of different people, and SleepExplorer could help users discover factors that are most relevant to their personal sleep.
影响因子：
5.6
作者：
Watson, Nathaniel F.;Badr, M. Safwan;Heald, Jonathan L.
通讯作者：
Heald, Jonathan L.
影响因子：
5.6
作者：
Buysse, Daniel J.
通讯作者：
Buysse, Daniel J.
影响因子：
4.1
作者：
Lichstein, KL;Durrence, HH;Riedel, BW
通讯作者：
Riedel, BW