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Recommender System Based on Fuzzy Reasoning and Information Systems

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Computational Collective Intelligence (ICCCI 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11055))

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Abstract

In this research a recommender system with possible applications in e-commerce, based on rule induction mechanism and fuzzy reasoning, is presented. The theoretical concept proposed assume the application of fuzzy sets in a procedure of rule induction, as an information generalization, in purpose to predict the degree of subjective customer satisfaction with respect to his previous reviews. The innovative idea lays in the transformation of decision rules into fuzzy rules, regarding to the basic Mamdani reasoning model. The research was verified on real data, i.e. customer reviews of different products.

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Notes

  1. 1.

    The price attribute may not be up-to-date, but it doesn’t change the concept proposed.

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Acknowledgement

I would like to thank to my student Jakub Salamon for the experiments provided.

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Authors and Affiliations

  1. Faculty of Computer Science and Management, Department of Computational Intelligence, Wroclaw University of Science and Technology, Wroclaw, Poland

    Martin Tabakov

Authors
  1. Martin Tabakov
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Correspondence to Martin Tabakov .

Editor information

Editors and Affiliations

  1. Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Ngoc Thanh Nguyen

  2. Department of Computer Science and Creative Technologies, University of the West of England, Bristol, United Kingdom

    Elias Pimenidis

  3. Department of Computer Science and Creative Technologies, University of the West of England, Bristol, United Kingdom

    Zaheer Khan

  4. Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

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Tabakov, M. (2018). Recommender System Based on Fuzzy Reasoning and Information Systems. In: Nguyen, N., Pimenidis, E., Khan, Z., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2018. Lecture Notes in Computer Science(), vol 11055. Springer, Cham. https://doi.org/10.1007/978-3-319-98443-8_23

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  • DOI: https://doi.org/10.1007/978-3-319-98443-8_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-98442-1

  • Online ISBN: 978-3-319-98443-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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