移动通知数据集的综合与评价

Kieran Fraser, Bilal Yousuf, Owen Conlan
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引用次数: 7

摘要

开源移动通知数据集在研究界是罕见的。由于移动通知的敏感性,很难找到一个数据集,以这样一种方式捕捉其特征,使其固有的个人信息保密。出于这个原因,通知管理领域的大多数研究都需要开发专门的软件来捕获测试假设、训练算法和评估拟议系统所需的数据。作为替代方案,本文讨论了利用大规模移动使用数据集来获得用于测试和改进智能通知管理系统(NMS)的综合移动通知数据集的过程、优点和局限性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Synthesis & Evaluation of a Mobile Notification Dataset
Open-source mobile notification datasets are a rarity in the research community. Due to the sensitive nature of mobile notifications it is difficult to find a dataset which captures their features in such a way that their inherently personal information is kept private. For this reason, the majority of research in the domain of Notification Management requires ad-hoc software to be developed for capturing the data necessary to test hypotheses, train algorithms and evaluate proposed systems. As an alternative, this paper discusses the process, advantages and limitations with harnessing a large-scale mobile usage dataset for deriving a synthetic mobile notification dataset used in testing and improving an intelligent Notification Management System (NMS).
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