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Titlebook: Logical Foundations for Cognitive Agents; Contributions in Hon Hector J. Levesque,Fiora Pirri Book 1999 Springer-Verlag Berlin Heidelberg 1

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樓主: broach
61#
發(fā)表于 2025-4-1 05:27:11 | 只看該作者
62#
發(fā)表于 2025-4-1 07:48:36 | 只看該作者
Sheila A. Mcllraithproposed and focus on topological structure alone. In addition to topology, node contents exist in real-world networks, and may help for community detection. Recently, some studies try to combine topological structure and node contents. However, it is difficult to address an inherent situation in re
63#
發(fā)表于 2025-4-1 10:55:48 | 只看該作者
64#
發(fā)表于 2025-4-1 15:03:26 | 只看該作者
Yves Lespérance,Kenneth Tam,Michael JenkinNatural Language Processing (NLP) tasks. However, these models yield an unsatisfactory results in domain scenarios, particularly in specialized fields like biomedical contexts, where they cannot amass sufficient semantics of domain terms. To tackle this problem, we present a semantic learning method
65#
發(fā)表于 2025-4-1 20:51:53 | 只看該作者
66#
發(fā)表于 2025-4-2 02:06:09 | 只看該作者
Fangzhen Lin methods focus on single-type item recommendations and offer limited explainability of their recommendations. In this paper, we propose a novel framework knowledge graph transformer network (KGTN) for explainable multiple types of item recommendation, which aims to recommend items with different for
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