Abstract
In this paper, an adaptive tool for providing suggestions during the information search process is presented. The tool uses case-based reasoning techniques to find the most useful suggestions for a given situation by comparing them to a case base of previous situations and adapting the solution. The tool can learn from user participation.
A small, preliminary evaluation showed a high acceptance of the tool, even if improvements are still needed.
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Kriewel, S., Fuhr, N. (2007). Adaptive Search Suggestions for Digital Libraries. In: Goh, D.HL., Cao, T.H., Sølvberg, I.T., Rasmussen, E. (eds) Asian Digital Libraries. Looking Back 10 Years and Forging New Frontiers. ICADL 2007. Lecture Notes in Computer Science, vol 4822. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77094-7_31
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DOI: https://doi.org/10.1007/978-3-540-77094-7_31
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