A Method to Identify Personal Desktop Activities

As people acquire much more personal information as a result of personal and work activities, the management of these information becomes a serious problem and an important research issue. Modeling personal desktop activities and identifying them are two basic problems for supporting activity-based operations. To the best of our knowledge there is no literature on formalizing and identifying desktop activity from personal information management perspective. There are a number of challenges to this work, including the fact that people exhibit personalized behaviors, have individual interests, needs and resources, no available experimental data set, etc. In this paper, we perform a user experiment to learn about user desktop activities in a personal information management context. We collected information access activities in a naturalistic setting and propose a conceptual activity model by analyzing features of user behaviors at their desktop computers. We present an effective and efficient method of automatically identifying desktop activities. To evaluate performance of our method, we develop a prototype system to collect real users activities, and evaluate our methods for identifying activities. The results verify the effectiveness and efficiency of our methods.