MyEvents: A Personal Visual Analytics Approach for Mining Key Events and Knowledge Discovery in Support of Personal Reminiscence

F. Parvinzamir, Y. Zhao, Z. Deng, F. Dong

Research output: Contribution to journalArticle

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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.

Original languageEnglish
Pages (from-to)647
Number of pages662
JournalComputer Graphics Forum
Issue number1
Early online date05 Jan 2019
Publication statusPublished - 15 Mar 2019



  • data mining
  • human–computer interfaces
  • interaction
  • methods and applications
  • visual analytics
  • visualization

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