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Something’s Missing? A Procedure for Extending Item Content Data Sets in the Context of Recommender Systems

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Heinrich, Bernd ; Hopf, Marcus ; Lohninger, Daniel ; Schiller, Alexander ; Szubartowicz, Michael
License: Creative Commons Attribution 4.0
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Date of publication of this fulltext: 29 Oct 2020 08:34

This publication is part of the DEAL contract with Springer.


The rapid development of e-commerce has led to a swiftly increasing number of competing providers in electronic markets, which maintain their own, individual data describing the offered items. Recommender systems are popular and powerful tools relying on this data to guide users to their individually best item choice. Literature suggests that data quality of item content data has substantial ...


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