Capturing unselfconscious information seeking behavior by analyzing gaze patterns via eye tracking experiments

In recent years, eye tracking has been widely applied in a variety of fields, such as web usability studies and psychological experiments. To develop a personalized system or network service, it is important to recognize and capture users´ needs, situations and contexts in order to create an effective user model. In this paper, we present an integrated approach on how to capture users´ unselfconscious information seeking behavior by analyzing their gaze patterns using an eye tracker. We describe the design of an eye tracking experiment, and analyze the eye tracking data to extract gaze patterns, which can be used for use modeling. We further discuss the experiment result and highlight our future work.