Large-Scale Mining, Discovery and Visualization of WWW User Clickpaths

Analysis of user clickstreams on the world wide web is made challenging by the volume of data and the difficulty of visualizing millions of different navigation paths. We present a method for identifying user clickpaths which scales well on large amounts of data, and provides an intuitive and insightful visual representation of user activity. Our technique borrows from the data mining literature on association rules and the computer graphics literature on graph layout optimization. The method is demonstrated with data from two commercial sources and paints a fascinating picture of web activity.