Abstract
The experimental results provided in this chapter correspond to the testing stage of our system. The evaluation process compared three recommendation approaches: (a) the standard Collaborative Filtering methodologies, (b) the Cascade Content-based Recommendation methodology and (c) the Cascade Hybrid Recommendation methodology. To evaluate our system, we tested its performance as a RS for music files. In the following sections of this chapter, a detailed description is provided of the three types of experiments that were conducted in order to evaluate the efficiency of our cascade recommendation architecture.
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© 2015 Springer International Publishing Switzerland
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Lampropoulos, A.S., Tsihrintzis, G.A. (2015). Evaluation of Cascade Recommendation Methods. In: Machine Learning Paradigms. Intelligent Systems Reference Library, vol 92. Springer, Cham. https://doi.org/10.1007/978-3-319-19135-5_7
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DOI: https://doi.org/10.1007/978-3-319-19135-5_7
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Publisher Name: Springer, Cham
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Online ISBN: 978-3-319-19135-5
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