The rapid growth of Internet usage has dramatically changed the way we interact with the outside world. Many people read news, communicate with friends and purchase goods online. These activities are usually done via web browsing, and web browsers record information about these activities. The recorded data can be used to understand web browsing behavior of users and improve their browsing experience. For example, website usability and the personalization of online services could both benefit from knowledge of user browsing behavior. A number of methods including data mining, text processing and visualization have been used to uncover user browsing patterns. However, these methods are mainly used to analyze and gain insights into collective behavior patterns of either a large amount of separate web users or users within an online community over a prolonged period of time. Very few systems are available for analyzing the detailed behavior of a single user within a relatively short and specific period of time. In an attempt to shorten this gap, we have developed a visual analytic system called WeBeVis. This system offers three different ways of visualizing web browsing data based on our proposed visual metaphors. It also provides a common interface for users to interact with the visualizations. In this paper, we describe this system and present a user study of it. We show that by visualizing the web browsing history of a user, we are able to uncover interesting patterns in the way that individuals use the web.
Huang, W., Khoury, R., Dawborn, T., Huang, B., Huang, M., & Huang, X. (2013). WeBeVis: Analyzing User Web Behavior through Visual Metaphors. Science in China, Series F: Information Sciences, 56(5), 1-15. https://doi.org/10.1007/s11432-013-4869-7