FRINK Linked Data Fragments server

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• W3021560003 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 as attribute values to the user of a configurator. This discussion is based on a working example from the domain of mobile phones." @default.
• W3021560003 created "2020-05-13" @default.
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• W3021560003 date "2014-01-01" @default.
• W3021560003 modified "2023-09-28" @default.
• W3021560003 title "Personalized Configuration" @default.
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• W3021560003 doi "https://doi.org/10.1016/b978-0-12-415817-7.00013-x" @default.
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