Search results
Results: 10
Number of items: 10
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Liu, Y., Li, M., Ariannezhad, M., Mansoury, M., Aliannejadi, M., & de Rijke, M. (2024). Measuring Item Fairness in Next Basket Recommendation: A Reproducibility Study. In N. Goharian, N. Tonellotto, Y. He, A. Lipani, G. McDonald, C. Macdonald, & I. Ounis (Eds.), Advances in Information Retrieval: 46th European Conference on Information Retrieval, ECIR 2024, Glasgow, UK, March 24–28, 2024 : proceedings (Vol. IV, pp. 210-225). (Lecture Notes in Computer Science; Vol. 14611). Springer. https://doi.org/10.1007/978-3-031-56066-8_18 -
Li, M., Liu, Y., Jullien, S., Ariannezhad, M., Yates, A., Aliannejadi, M., & de Rijke, M. (2024). Are We Really Achieving Better Beyond-Accuracy Performance in Next Basket Recommendation? In SIGIR '24: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 14-18, 2024, Washington, DC, USA (pp. 924-934). Association for Computing Machinery. https://doi.org/10.1145/3626772.3657835
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Jullien, S., Ariannezhad, M., Groth, P., & Rijke, M. D. (2023). A Simulation Environment and Reinforcement Learning Method for Waste Reduction. Transactions on Machine Learning Research, 2023, Article 769. https://openreview.net/forum?id=KSvr8A62MD
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Ariannezhad, M., Jullien, S., Li, M., Fang, M., Schelter, S., & de Rijke, M. (2022). ReCANet: A Repeat Consumption-Aware Neural Network for Next Basket Recommendation in Grocery Shopping. In SIGIR '22: proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 11-15, 2022, Madrid, Spain (pp. 1240-1250). The Association for Computing Machinery. https://doi.org/10.1145/3477495.3531708
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Ariannezhad, M. (2022). Understanding and Learning from User Behavior for Recommendation in Multi-channel Retail. In M. Hagen, S. Verberne, C. Macdonald, C. Seifert, K. Balog, K. Nørvåg, & V. Setty (Eds.), Advances in Information Retrieval: 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022 : proceedings (Vol. II, pp. 455-462). (Lecture Notes in Computer Science; Vol. 13186). Springer. https://doi.org/10.1007/978-3-030-99739-7_56
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Ariannezhad, M., Yahya, M., Meij, E., Schelter, S., & de Rijke, M. (2022). Understanding Financial Information Seeking Behavior from User Interactions with Company Filings. In WWW '22 Companion: companion proceedings of the Web Conference 2022: April 25, 2022, Lyon, France (pp. 586-594). Association for Computing Machinery. https://doi.org/10.1145/3487553.3524636
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Ariannezhad, M., Jullien, S., Nauts, P., Fang, M., Schelter, S., & de Rijke, M. (2021). Understanding Multi-Channel Customer Behavior in Retail. In CIKM '21: proceedings of the 30th ACM International Conference on Information & Knowledge Management : November 1-5, 2021, virtual event, Australia (pp. 2867–2871). The Association for Computing Machinery. https://doi.org/10.1145/3459637.3482208
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van de Looij, T., & Ariannezhad, M. (2021). Cluster-Based Forecasting for Intermittent and Non-intermittent Time Series. In V. Lemaire, S. Malinowski, A. Bagnall, T. Guyet, R. Tavenard, & G. Ifrim (Eds.), Advanced Analytics and Learning on Temporal Data: 6th ECML PKDD Workshop, AALTD 2021, Bilbao, Spain, September 13, 2021 : revised selected papers (pp. 139-154). (Lecture Notes in Computer Science; Vol. 13114), (Lecture Notes in Artificial Intelligence). Springer. https://doi.org/10.1007/978-3-030-91445-5_9
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Ariannezhad, M., Schelter, S., & de Rijke, M. (2020). Demand Forecasting in the Presence of Privileged Information. In V. Lemaire, S. Malinowski, A. Bagnall, T. Guyet, R. Tavenard, & G. Ifrim (Eds.), Advanced Analytics and Learning on Temporal Data: 5th ECML PKDD Workshop, AALTD 2020, Ghent, Belgium, September 18, 2020 : revised selected papers (pp. 46-62). (Lecture Notes in Computer Science; Vol. 12588), (Lecture Notes in Artificial Intelligence). Springer. https://doi.org/10.1007/978-3-030-65742-0_4
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