Abstract
The main source of information in most adaptive hypermedia systems are server monitored events such as page visits and link selections. One drawback of this approach is that pages are treated as “monolithic” entities, since the system cannot determine what portions may have drawn the user’s attention. Departing from this model, the work described here demonstrates that client-side monitoring and interpretation of users’ interactive behavior (such as mouse moves, clicks and scrolling) allows for detailed and significantly accurate predictions on what sections of a page have been looked at. More specifically, this paper provides a detailed description of an algorithm developed to predict which paragraphs of text in a hypertext document have been read, and to which extent. It also describes the user study, involving eye-tracking for baseline comparison, that served as the basis for the algorithm.
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Hauger, D., Paramythis, A., Weibelzahl, S. (2011). Using Browser Interaction Data to Determine Page Reading Behavior. In: Konstan, J.A., Conejo, R., Marzo, J.L., Oliver, N. (eds) User Modeling, Adaption and Personalization. UMAP 2011. Lecture Notes in Computer Science, vol 6787. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22362-4_13
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DOI: https://doi.org/10.1007/978-3-642-22362-4_13
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