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AMORE: design and implementation of a commercial-strength parallel hybrid movie recommendation engine

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Abstract

AMORE is a hybrid recommendation system that provides movie recommendation functionality to video-on-demand subscribers of a major triple-play service provider in Greece. Without any user relevance feedback for movies available, all recommendations are solely based on the users’ viewing history. To overcome such limitations as well as the extra problem of user histories that are usually the merger of the preferences of all persons in each household, we have performed extensive experiments with open-source recommendation software such as Apache Mahout and Lens-Kit, as well as with our own implementations of several user-based, item-based, and content-based recommendation algorithms. Our results indicate that our own custom multi-threaded implementation of collaborative filtering combined with a custom content-based algorithm outperforms current state-of-the-art implementations of similar algorithms both in solution quality and in response time by margins exceeding 100 % in terms of recall quality and 6300 % in terms of running time. The hybrid nature of the ensemble allows the system to perform well and to overcome inherent limitations of collaborative filtering, such as various cold-start problems. AMORE has been deployed in a production environment where it has contributed to an increase in the provider’s rental profits, while at the same time offers customer retention support.

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Acknowledgments

The authors would like to thank Hellas On Line S.A. for providing the industrial grant that made this research possible.

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Authors and Affiliations

  1. Athens Information Technology, 44 Kifisias Ave, Monumental Plaza, Bld. C, Marousi, 15125, Greece

    Ioannis T. Christou & Emmanouil Amolochitis

  2. CTiF, Aalborg University, Niels Jernes Vej 12, 9220, Aalborg, Denmark

    Emmanouil Amolochitis

  3. Department of Electronic Systems, Aalborg University, Niels Jernes Vej 12, 9220, Aalborg, Denmark

    Zheng-Hua Tan

Authors
  1. Ioannis T. Christou
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  2. Emmanouil Amolochitis
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  3. Zheng-Hua Tan
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Correspondence to Ioannis T. Christou.

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Christou, I.T., Amolochitis, E. & Tan, ZH. AMORE: design and implementation of a commercial-strength parallel hybrid movie recommendation engine. Knowl Inf Syst 47, 671–696 (2016). https://doi.org/10.1007/s10115-015-0866-z

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  • DOI: https://doi.org/10.1007/s10115-015-0866-z

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