Algorithms for Behavior-Based Recommender Systems

Part of the Contributions to Management Science book series (MANAGEMENT SC.)

Different methodologies exist for the generation of behavior-based recommendations. This chapter focuses on methods that are especially suited to the needs and challenges associated with the application area of STI providers. The behavioral input data consists of market baskets that can be found likewise in e-commerce, library environments, or (Web 2.0) social network sites. The relevant problem that has to be solved is the question, which co-purchases or co-inspections of products in the market baskets occur non-randomly thus hinting at an underlying relation of these products. First, a method developed for large samples based on calculating inspection frequency distribution functions following a logarithmic series distribution is presented.


Association Rule Recommender System Recommendation Service Market Basket Cold Start Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Physica-Verlag Heidelberg 2009

Authors and Affiliations

  1. 1.Universität Karlsruhe Fak. Wirtschaftswissenschaften Inst. InformationswirtschaftGermany

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