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Evaluation of Cascade Recommendation Methods

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Machine Learning Paradigms

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 92))

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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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Correspondence to Aristomenis S. Lampropoulos .

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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

  • Print ISBN: 978-3-319-19134-8

  • Online ISBN: 978-3-319-19135-5

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