Thyme: Improving Smartphone Prompt Timing Through Activity Awareness

Thyme: Improving Smartphone Prompt Timing Through Activity Awareness
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Thyme:通过活动意识改善智能手机提示时间

DOI:
10.1109/icmla.2017.0-141
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发表时间:
2017
期刊:
2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA)
影响因子:
--
通讯作者:
L. Holder
L. Holder
中科院分区:
--
文献类型:
--
作者:
S. Aminikhanghahi;Ramin Fallahzadeh;M. Sawyer;D. Cook;L. Holder

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智能手机的提示和通知很受欢迎,因为它们为用户提供了及时和重要的信息。然而,如果它们在不合适的时间突然出现并中断重要任务,它们也会成为一种烦恼。在本文中,我们介绍了Thyme,这是一个智能通知前端,它使用活动识别和机器学习来识别提示智能手机用户的最佳时间。我们评估的性能的活动意识的提示方法的基础上,47名参与者与固定的时间和基于胸腺的提示。我们的研究结果表明,使用这种智能方法对基于智能手机的提示进行计时,响应性从12.8%提高到93.2%。
Smartphone prompts and notifications are popular because they provide users with timely and important information. However, they can also be an annoyance if they pop up at inopportune times and interrupt important tasks. In this paper, we introduce Thyme, an intelligent notification front end that uses activity recognition and machine learning to identify the best times to prompt smartphone users. We evaluate the performance of an activity-aware prompting approach based on 47 participants with fixed time and Thyme-based prompts. Our results show that responsiveness improves from 12.8% to 93.2% using this intelligent approach to the timing of smartphone-based prompts.
DOI: 10.1145/2499621
发表时间: 2014-01-01
影响因子: 16.6
作者:
Bulling, Andreas;Blanke, Ulf;Schiele, Bernt
通讯作者: Schiele, Bernt