Personalized Configuration
Juha Tiihonena, Alexander Felfernigb and Monika Mandlb, aAalto University, Aalto, Finland, bGraz University of Technology, Graz, Austria
Abstract
The increasing size and complexity of products (or product assortments) triggers a demand for intelligent techniques that proactively support users of configurator applications in finding a solution (configuration) that fits their wishes and needs. Recommendation technologies are predestined to be applied in the configuration context, because they can find relevant items from large and complex item sets. In this chapter, we show how different types of basic recommendation technologies can be applied to recommend configurations or individual selections such ...
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