Abstract
Recently we presented a novel approach to the discovery of recommendation rules from a product case base that take account of all features of a recommended product, including those with respect to which the user’s preferences are unknown. In this paper, we investigate the potential role of default preferences in the discovery of recommendation rules. As we show in the domain of digital cameras, the potential benefits include a dramatic reduction in the effective length of the discovered rules and increased coverage of queries representing the user’s personal preferences. Another important finding of the research presented is that in a recommender system that takes account of default preferences, many of the products in the case base may never be recommended.
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McSherry, D., Stretch, C. (2006). Recommendation Knowledge Discovery. In: Bramer, M., Coenen, F., Allen, T. (eds) Research and Development in Intelligent Systems XXII. SGAI 2005. Springer, London. https://doi.org/10.1007/978-1-84628-226-3_19
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DOI: https://doi.org/10.1007/978-1-84628-226-3_19
Publisher Name: Springer, London
Print ISBN: 978-1-84628-225-6
Online ISBN: 978-1-84628-226-3
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