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Learning Joint Relational Co-evolution in Spatial-Temporal Knowledge Graph for SMEs Supply Chain Prediction., , , , , , , и . KDD, стр. 4426-4436. ACM, (2023)Towards Open-World Cross-Domain Sequential Recommendation: A Model-Agnostic Contrastive Denoising Approach., , , , , , , , , и . ECML/PKDD (1), том 14941 из Lecture Notes in Computer Science, стр. 161-179. Springer, (2024)Information Maximization via Variational Autoencoders for Cross-Domain Recommendation., , , , , , , и . CoRR, (2024)Task Aware Feature Extraction Framework for Sequential Dependence Multi-Task Learning., , , , , , , и . RecSys, стр. 151-160. ACM, (2023)Selective and collaborative influence function for efficient recommendation unlearning., , , , , , и . Expert Syst. Appl., (декабря 2023)Towards Open-world Cross-Domain Sequential Recommendation: A Model-Agnostic Contrastive Denoising Approach., , , , , , , , , и . CoRR, (2023)Rethinking Cross-Domain Sequential Recommendation under Open-World Assumptions., , , , , , , и . WWW, стр. 3173-3184. ACM, (2024)Fine-Tuning Large Language Model Based Explainable Recommendation with Explainable Quality Reward., , , , , , , , и . AAAI, стр. 9250-9259. AAAI Press, (2024)Exploring Large-Scale Financial Knowledge Graph for SMEs Supply Chain Mining., , , , , , , и . IEEE Trans. Knowl. Data Eng., 36 (5): 1979-1990 (мая 2024)Neural Node Matching for Multi-Target Cross Domain Recommendation., , , , , , , и . ICDE, стр. 2154-2166. IEEE, (2023)