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Data Quality in Recommender Systems: The Impact of Completeness of Item Content Data on Prediction Accuracy of Recommender Systems

Heinrich, Bernd ; Hopf, Marcus ; Lohninger, Daniel ; Schiller, Alexander ; Szubartowicz, Michael


Recommender systems strive to guide users, especially in the field of e-commerce, to their individually best choice when a large number of alternatives is available. In general, literature suggests that the quality of data which a recommender system is based on may have important impact on recommendation quality. In this paper, we focus on the data quality dimension completeness of item content ...


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