Explaining the user experience of recommender systems von Knijnenburg, Bart P., Willemsen, Martijn C., Gantner, Zeno, Soncu, Hakan, Newell, Chris

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Learning Attribute-to-Feature Mappings for Cold-Start Recommendations von Gantner, Z, Drumond, L, Freudenthaler, C, Rendle, S, Schmidt-Thieme, L

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Ideas and Improvements for Semantic Wikis von Fischer, Jochen, Gantner, Zeno, Rendle, Steffen, Stritt, Manuel, Schmidt-Thieme, Lars

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Cost-sensitive learning methods for imbalanced data von Thai-Nghe, Nguyen, Gantner, Zeno, Schmidt-Thieme, Lars

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A new evaluation measure for learning from imbalanced data von Nguyen Thai-Nghe, Gantner, Z., Schmidt-Thieme, L.

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Classification and Data Mining von Giusti, Antonio, Ritter, Gunter, Vichi, Maurizio

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BPR: Bayesian Personalized Ranking from Implicit Feedback von Rendle, Steffen, Freudenthaler, Christoph, Gantner, Zeno, Schmidt-Thieme, Lars

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An Evaluation Measure for Learning from Imbalanced Data Based on Asymmetric Beta Distribution von Thai-Nghe, Nguyen, Gantner, Zeno, Schmidt-Thieme, Lars

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BPR: Bayesian Personalized Ranking from Implicit Feedback von Rendle, Steffen, Freudenthaler, Christoph, Gantner, Zeno, Schmidt-Thieme, Lars

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Supervised Machine Learning Methods for Item Recommendation von Gantner, Zeno

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