Abstract
The traditional paradigm for Web interactions, where the interactions are server-driven rather than user-driven, has limitations that are becoming increasingly apparent. The Personal Web proposes to provide intelligent services that support a more user-centric interaction paradigm in order to allow the user to more easily assemble and aggregate web elements to accomplish specific tasks.
In this paper we examine the role predictive analytics can play in intelligent services supporting decision-making tasks and describe the Predictive Analytics in Smart Interactions Framework (PASIF), which is a framework for incorporating predictive analytics into intelligent services. PASIF achieves effective levels of support in the dynamic real-time environment of the Personal Web by incorporating ensemble models and techniques to detect and adapt to concept drift in the data sources.
This research is supported by the Centre for Advanced Studies, IBM Canada Ltd. and MITACS.
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Matheson, M., Martin, P., Lo, J., Ng, J., Tan, D., Thomson, B. (2013). Intelligence for the Personal Web. In: Chignell, M., Cordy, J.R., Kealey, R., Ng, J., Yesha, Y. (eds) The Personal Web. Lecture Notes in Computer Science, vol 7855. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39995-4_6
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DOI: https://doi.org/10.1007/978-3-642-39995-4_6
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