Integrating Graph Retrieval-Augmented Generation into Prescriptive Recommender Systems
M. Niederhaus, N. Migenda, J. Weller, M. Kohlhase, W. Schenck, Big Data and Cognitive Computing 9 (2025).
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Big Data and Cognitive Computing
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9
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10
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261
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Article Processing Charge funded by the Deutsche Forschungsgemeinschaft and the Open Access Publication Fund of LibreCat University.
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Niederhaus, Marvin ; Migenda, Nico ; Weller, Julian ; Kohlhase, Martin ; Schenck, Wolfram: Integrating Graph Retrieval-Augmented Generation into Prescriptive Recommender Systems. In: Big Data and Cognitive Computing Bd. 9, MDPI AG (2025), Nr. 10
Niederhaus M, Migenda N, Weller J, Kohlhase M, Schenck W. Integrating Graph Retrieval-Augmented Generation into Prescriptive Recommender Systems. Big Data and Cognitive Computing. 2025;9(10). doi:10.3390/bdcc9100261
Niederhaus, M., Migenda, N., Weller, J., Kohlhase, M., & Schenck, W. (2025). Integrating Graph Retrieval-Augmented Generation into Prescriptive Recommender Systems. Big Data and Cognitive Computing, 9(10). https://doi.org/10.3390/bdcc9100261
@article{Niederhaus_Migenda_Weller_Kohlhase_Schenck_2025, title={Integrating Graph Retrieval-Augmented Generation into Prescriptive Recommender Systems}, volume={9}, DOI={10.3390/bdcc9100261}, number={10261}, journal={Big Data and Cognitive Computing}, publisher={MDPI AG}, author={Niederhaus, Marvin and Migenda, Nico and Weller, Julian and Kohlhase, Martin and Schenck, Wolfram}, year={2025} }
Niederhaus, Marvin, Nico Migenda, Julian Weller, Martin Kohlhase, and Wolfram Schenck. “Integrating Graph Retrieval-Augmented Generation into Prescriptive Recommender Systems.” Big Data and Cognitive Computing 9, no. 10 (2025). https://doi.org/10.3390/bdcc9100261.
M. Niederhaus, N. Migenda, J. Weller, M. Kohlhase, and W. Schenck, “Integrating Graph Retrieval-Augmented Generation into Prescriptive Recommender Systems,” Big Data and Cognitive Computing, vol. 9, no. 10, 2025.
Niederhaus, Marvin, et al. “Integrating Graph Retrieval-Augmented Generation into Prescriptive Recommender Systems.” Big Data and Cognitive Computing, vol. 9, no. 10, 261, MDPI AG, 2025, doi:10.3390/bdcc9100261.
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