Clickstreams are among the most popular data sources because Web servers automatically record each action and the Web log entries promise to add up to a comprehensive description of behaviors of users. Clickstreams, however, are large and raise a number of unique challenges with respect to visual data mining. At the technical level the huge amount of data requires scalable solutions and limits the presentation to summary and model data. Equally challenging is the interpretation of the data at the conceptual level. Many analysis tools are able to produce different types of statistical charts. However, the step from statistical charts to comprehensive information about customer behavior is still largely unresolved. We propose a density surface based analysis of 3D data that uses state-of-the-art interaction techniques to explore the data at various granularities. © 2008 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Böhlen, M. H., Bukauskas, L., Mazeika, A., & Mylov, P. (2008). The 3DVDM approach: A case study with clickstream data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4404 LNCS, pp. 13–29). https://doi.org/10.1007/978-3-540-71080-6_2
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