KEA: practical automatic keyphrase extraction
Proceedings of the fourth ACM conference on Digital libraries
SWISH: semantic analysis of window titles and switching history
Proceedings of the 11th international conference on Intelligent user interfaces
Detecting and correcting user activity switches: algorithms and interfaces
Proceedings of the 14th international conference on Intelligent user interfaces
Real-time detection of task switches of desktop users
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
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An average white-collar worker deals with enormous amount of digital information on daily basis. Recently, there has been a growing interest to support their work. However, in order to be really supportive there is a need to know the current activity of the user at all times. In this paper we present a new technique that takes advantage of temporal aspects of user activity behavior to infer when it is most likely that an activity switch is occurring. We then describe "Activity Switch Detector" an interactive switch notification system embodying these ideas, and an extensive user study by ten participants to test the validity of the approach and present its results.