Abstract
Hybrid recommender systems combine recommendation components of different types to achieve improved performance. Many such hybrids have been built but recent studies show that hybrids using case- based recommendation are rare. This paper shows how a range of different hybrids can be constructed using a case-based recommender as one component, and describes a series of experiments in which 20 different hybrids are built and evaluated. Cascade and feature augmentation hybrids are shown to have the highest accuracy over a range of different profile sizes.
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Burke, R. (2004). Hybrid Recommender Systems with Case-Based Components. In: Funk, P., González Calero, P.A. (eds) Advances in Case-Based Reasoning. ECCBR 2004. Lecture Notes in Computer Science(), vol 3155. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28631-8_8
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DOI: https://doi.org/10.1007/978-3-540-28631-8_8
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