Abstract
Most clickstream visualization techniques display web users’ clicks by highlighting paths in a graph of the underlying web site structure. These techniques do not scale to handle high volume web usage data. Further, historical usage data is not considered. The work described in this paper differs from other work in the following aspect. Fuzzy clustering is applied to historical usage data and the result imaged in the form of a point cloud. Web navigation data from active users are shown as animated paths in this point cloud. It is clear that when many paths get attracted to one of the clusters, that particular cluster is currently “hot.” Further as sessions terminate, new sessions are incrementally incorporated into the point cloud. The complete process is closely coupled to the fuzzy clustering technique and makes effective use of clustering results. The method is demonstrated on a very large set of web log records consisting of over half a million page clicks.
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Kannappady, S., Mudur, S.P., Shiri, N. (2006). Clickstream Visualization Based on Usage Patterns. In: Kalra, P.K., Peleg, S. (eds) Computer Vision, Graphics and Image Processing. Lecture Notes in Computer Science, vol 4338. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11949619_31
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DOI: https://doi.org/10.1007/11949619_31
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