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Adversarial Explanations for Knowledge Graph Embeddings
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022We propose a novel black-box approach for performing adversarial attacks against knowledge graph embedding models. An adversarial attack is a small perturbation of the data at training time to cause model failure at test time. We make use of an efficient rule learning approach and use abductive reasoning to identify triples which are logical ...
Betz, Patrick +2 more
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Capturing Knowledge Graph Embeddings
2020In this chapter we focus on knowledge graph embeddings, an approach to produce embeddings for concepts and names that are the main nodes in knowledge graphs, as well as the relations between them. The resulting embeddings aim to capture the knowledge encoded in the structure of the graph, in terms of how nodes are related to one another. This technique
Jose Manuel Gomez-Perez +2 more
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Knowledge Graph Confidence-Aware Embedding for Recommendation
Neural NetworksKnowledge graphs (KG) are vital for extracting and storing knowledge from large datasets. Current research favors knowledge graph-based recommendation methods, but they often overlook the features learning of relations between entities and focus excessively on entity-level details. Moreover, they ignore a crucial fact: the aggregation process of entity
Chen Huang +5 more
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Knowledge Graphs 2023 - 6.2 Knowledge Graph Embeddings
2023Sack, Harald, Tan, Mary Ann
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Learning Knowledge Graph Embedding With Heterogeneous Relation Attention Networks
IEEE Transactions on Neural Networks and Learning Systems, 2022Zhifei Li, Hai Liu, Zhaoli Zhang
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Multi-Scale Dynamic Convolutional Network for Knowledge Graph Embedding
IEEE Transactions on Knowledge and Data Engineering, 2022Zhaoli Zhang, Zhifei Li, Hai Liu
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Learning knowledge graph embedding with a dual-attention embedding network
Expert Systems With Applications, 2023海川 方, Youwei Wang, Yangdong Ye
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JointE: Jointly utilizing 1D and 2D convolution for knowledge graph embedding
Knowledge-Based Systems, 2022Defang Chen
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Federated knowledge graph completion via embedding-contrastive learning
Knowledge-Based Systems, 2022Mingyang Chen
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