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Recommender Systems Handbook pp 161–190Cite as

Constraint-Based Recommender Systems

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Abstract

Recommender systems provide valuable support for users who are searching for products in e-commerce environments. Research in the field long focused on rating-based algorithms supporting the recommendation of quality and taste products such as news, books, or movies. The recommendation of more complex products such as financial services or electronic consumer goods however requires additional types of knowledge to be encoded in a recommender system. Constraint-based approaches are particularly well suited and can make the product selection process more effective in such domains. In this chapter, we review constraint-based recommendation approaches and provide an overview of technologies for the development of knowledge bases for constraint-based recommenders since appropriate tool support can be crucial in practical settings. We furthermore discuss possible forms of user interaction that are supported by constraint-based recommender applications, report scenarios in which constraint-based recommenders have been successfully applied, and review different technical solution approaches. An outline of possible directions for future research concludes this chapter.

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Notes

  1. 1.

    Utility-based recommenders are often categorized as being knowledge-based, too [5]. For a detailed discussion of utility-based approaches, see [5, 19].

  2. 2.

    For simplicity, we omit the specification of V PROD , C F , and C PROD .

  3. 3.

    The general idea of exploring a database by criticizing successive examples is in fact much older and was already proposed in the early 1980s in an information-retrieval context [73].

  4. 4.

    For an overview of related similarity metrics we refer to [53].

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Authors and Affiliations

  1. Graz University of Technology, Graz, Austria

    Alexander Felfernig

  2. Alpen-Adria-Universitaet Klagenfurt, Klagenfurt, Austria

    Gerhard Friedrich & Markus Zanker

  3. TU Dortmund, Dortmund, Germany

    Dietmar Jannach

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  1. Alexander Felfernig
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  2. Gerhard Friedrich
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  3. Dietmar Jannach
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  4. Markus Zanker
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Correspondence to Alexander Felfernig .

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Editors and Affiliations

  1. Faculty of Computer Science, Free University of Bozen-Bolzano, Bolzano - Bozen, Italy

    Francesco Ricci

  2. Information Systems Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel

    Lior Rokach

  3. Ben-Gurion University of the Negev, Beer-Sheva, Israel

    Bracha Shapira

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Felfernig, A., Friedrich, G., Jannach, D., Zanker, M. (2015). Constraint-Based Recommender Systems. In: Ricci, F., Rokach, L., Shapira, B. (eds) Recommender Systems Handbook. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7637-6_5

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