MyEvents: A Personal Visual Analytics Approach for Mining Key Events and Knowledge Discovery in Support of Personal Reminiscence
MyEvents: A Personal Visual Analytics Approach for Mining Key Events and Knowledge Discovery in Support of Personal Reminiscence
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DOI：
10.1111/cgf.13596
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发表时间：
2019-01
影响因子：
2.5
通讯作者：
Farzad Parvinzamir;Youbing Zhao;Zhikun Deng;Feng Dong
中科院分区：
文献类型：
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作者：
Farzad Parvinzamir;Youbing Zhao;Zhikun Deng;Feng Dong
回忆是我们生活中的一个重要方面。它保留了珍贵的记忆，让我们形成自己的身份，并鼓励我们接受过去。我们的工作利用现代传感器技术来支持回忆，使日常的个人活动和个人运动在空间和时间的自我监测。本文介绍了MyEvents，这是一个为非计算专家设计的基于Web的个人视觉分析平台，可以收集长期的位置和移动数据，并生成事件纪念品。我们的研究集中在事件回忆中的两个突出目标：（1）选择主观性和人类参与自我知识发现和纪念品创造的过程;（2）通过呈现目标事件及其相关信息来增强事件熟悉度，以实现最佳记忆回忆和回忆。提出了一种新的多重要性事件排序模型，根据用户对事件类别、频率和规律的偏好来确定个人历史中的重要事件。评估结果表明，MyEvents有效地实现了回忆的目标和任务。
Reminiscence is an important aspect in our life. It preserves precious memories, allows us to form our own identities and encourages us to accept the past. Our work takes the advantage of modern sensor technologies to support reminiscence, enabling self‐monitoring of personal activities and individual movement in space and time on a daily basis. This paper presents MyEvents, a web‐based personal visual analytics platform designed for non‐computing experts, that allows for the collection of long‐term location and movement data and the generation of event mementos. Our research is focused on two prominent goals in event reminiscence: (1) selection subjectivity and human involvement in the process of self‐knowledge discovery and memento creation; and (2) the enhancement of event familiarity by presenting target events and their related information for optimal memory recall and reminiscence. A novel multi‐significance event ranking model is proposed to determine significant events in the personal history according to user preferences for event category, frequency and regularity. The evaluation results show that MyEvents effectively fulfils the reminiscence goals and tasks.