In this paper, we present a novel approach to track user interaction on a web page based on JavaScript-events combined with the Semantic Web standard Microformats to obtain more fine-grained and meaningful user information. Today's user tracking solutions are mostly page-based and lose valuable information about user interactions. To get an in-depth understanding of user's interests and intentions from observing him while interacting on a website, interaction data needs to be tracked on an event rather than on a page basis enhanced with semantic knowledge to understand the user intention. Our goal is to create an easy-to-integrate user tracker that is capable of collecting tracking information of configurable depth and feeding a highly sophisticated user model needed to provide personalized services such as recommendation and search. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Plumbaum, T., Stelter, T., & Korth, A. (2009). Semantic web usage mining: Using semantics to understand user intentions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5535 LNCS, pp. 391–396). https://doi.org/10.1007/978-3-642-02247-0_42
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