Publication: Evaluation of Algorithms for Interaction-Sparse Recommendations: Neural Networks don’t Always Win
Evaluation of Algorithms for Interaction-Sparse Recommendations: Neural Networks don’t Always Win
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Klingler, Y., Lehmann, C., Monteiro, J. P., Saladin, C., Bernstein, A., & Stockinger, K. (2022). Evaluation of Algorithms for Interaction-Sparse Recommendations: Neural Networks don’t Always Win. Advances in Database Technology, 475–486. https://doi.org/10.48786/edbt.2022.42
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In recent years, top-K recommender systems with implicit feed-back data gained interest in many real-world business scenarios. In particular, neural networks have shown promising results on these tasks. However, while traditional recommender systems are built on datasets with frequent user interactions, insurance recommenders often have access to a very limited amount of user interactions, as people only buy a few insurance products.
In this paper, we shed new light on the problem of top-K recommendations for interaction-sparse recom
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Klingler, Y., Lehmann, C., Monteiro, J. P., Saladin, C., Bernstein, A., & Stockinger, K. (2022). Evaluation of Algorithms for Interaction-Sparse Recommendations: Neural Networks don’t Always Win. Advances in Database Technology, 475–486. https://doi.org/10.48786/edbt.2022.42
