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Knowledge Graphs 2023 - 6.2 Knowledge Graph Embeddings
2023Sack, Harald, Tan, Mary Ann
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Frameless Graph Knowledge Distillation
IEEE Transactions on Neural Networks and Learning SystemsKnowledge distillation (KD) has shown great potential for transferring knowledge from a complex teacher model to a simple student model in which the heavy learning task can be accomplished efficiently and without losing too much prediction accuracy. Recently, many attempts have been made by applying the KD mechanism to graph representation learning ...
Dai Shi +4 more
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Knowledge Graphs: Opportunities and Challenges
Artificial Intelligence Review, 2023Ciyuan Peng, Feng Xia, Francesco Osborne
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A Survey on Knowledge Graphs: Representation, Acquisition, and Applications
IEEE Transactions on Neural Networks and Learning Systems, 2022Shaoxiong Ji, Shirui Pan, Erik Cambria
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Semantic Knowledge Graphs for the News: A Review
ACM Computing Surveys, 2023Andreas L Opdahl +2 more
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Heterogeneous relational reasoning in knowledge graphs with reinforcement learning
Information Fusion, 2022Steven Krieg, Chuxu Zhang, Meng Jiang
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An Embedding-Based Approach to Rule Learning in Knowledge Graphs
IEEE Transactions on Knowledge and Data Engineering, 2021Pouya Ghiasnezhad Omran +2 more
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