Constraint-based Recommendation

Recommender systems provide valuable support for users who are searching for products and services in e-commerce environments. Research in the field long focused on algorithms supporting the recommendation of quality&taste products such as news, books, or movies. Nowadays, the scope of those systems is extended to complex product domains such as financial services or electronic consumer goods. Constraint-based recommenders are particularly well suited as they support effective product and service selection processes in such domains. In this chapter, we characterize constraint-based recommendation problems and provide an overview of major technologies that support the development of knowledge bases for constraint-based recommenders which is of high importance for a successful application in commercial settings. Thereafter we give an overview of intelligent interaction mechanisms which are supported by constraint-based recommender applications and discuss scenarios where constraint-based recommenders have been successfully applied in commercial environments. Finally, this chapter is concluded with an outline of open research issues. Alexander Felfernig Graz University of Technology e-mail: [email protected] Gerhard Friedrich University Klagenfurt e-mail: [email protected] Dietmar Jannach TU Dortmund e-mail: [email protected] Markus Zanker University Klagenfurt e-mail: [email protected]