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International Conference on Neural Information Processing

ICONIP 2019: Neural Information Processing pp 717–724Cite as

On Explainable Flexible Fuzzy Recommender and Its Performance Evaluation Using the Akaike Information Criterion

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1142))

Abstract

In the paper, fuzzy recommender systems are proposed based on the novel method for nominal attribute coding. Several flexibility parameters - subjects to learning - are incorporated to their construction, allowing systems to better represent patterns encoded in data. The learning process does not affect the initial interpretable form of fuzzy recommenders rules. Using the Akaike Information Criterion allows evaluating the trade-off between a number of rules and interpretability which is crucial to provide proper explanations for users.

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Acknowledgments

– This research was supported by the Polish National Science Center grants 2015/19/B/ST6/03179.

– The project financed under the program of the Minister of Science and Higher Education under the name “Regional Initiative of Excellence" in the years 2019-2022, project number 020/RID/2018/19, the amount of financing 12,000,000 PLN.

Author information

Authors and Affiliations

  1. Senfino, 1412 Broadway 21st floor, New York City, NY, 10018, USA

    Tomasz Rutkowski

  2. Polish-Japanese Academy of Information Technology, Koszykowa 86, 02-008, Warsaw, Poland

    Tomasz Rutkowski & Radosław Nielek

  3. Institute of Computational Intelligence, Czestochowa University of Technology, Al. Armii Krajowej 36, 42-200, Czestochowa, Poland

    Krystian Łapa & Maciej Jaworski

  4. Information Technology Institute, University of Social Sciences, Lodz, Poland

    Danuta Rutkowska

Authors
  1. Tomasz Rutkowski
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  2. Krystian Łapa
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  3. Maciej Jaworski
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  4. Radosław Nielek
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  5. Danuta Rutkowska
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Corresponding author

Correspondence to Tomasz Rutkowski .

Editor information

Editors and Affiliations

  1. Australian National University, Canberra, ACT, Australia

    Tom Gedeon

  2. Murdoch University, Murdoch, WA, Australia

    Kok Wai Wong

  3. Kyungpook National University, Daegu, Korea (Republic of)

    Minho Lee

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Rutkowski, T., Łapa, K., Jaworski, M., Nielek, R., Rutkowska, D. (2019). On Explainable Flexible Fuzzy Recommender and Its Performance Evaluation Using the Akaike Information Criterion. In: Gedeon, T., Wong, K., Lee, M. (eds) Neural Information Processing. ICONIP 2019. Communications in Computer and Information Science, vol 1142. Springer, Cham. https://doi.org/10.1007/978-3-030-36808-1_78

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  • DOI: https://doi.org/10.1007/978-3-030-36808-1_78

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-36807-4

  • Online ISBN: 978-3-030-36808-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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