Towards Data Poisoning Attack against Knowledge Graph Embedding.pdf - 源码 - 源码 - 免费下载

Towards Data Poisoning Attack against Knowledge Graph Embedding.pdf

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资源说明：Knowledge graph embedding (KGE) is a technique for learning continuousembeddingsfor entities and relations in the knowledge graph. Due to its beneﬁt to a variety of downstream tasks such as knowledge graph completion, question answering and recommendation, KGE has gained signiﬁcant attention recently. Despite its effectiveness in a benign environment, KGE’s robustness to adversarialattacks is not well-studied. Existing attack methods on graph data cannot be directly applied to attack the embeddings of knowledge graph due to its heterogeneity. To ﬁll this gap, we propose a collection of data poisoning attack strategies, which can effectively manipulate the plausibility of arbitrary targeted facts in a knowledge graph by adding or deleting facts on the graph. The effectiveness and efﬁciency of the proposed attack strategies are veriﬁed by extensive evaluations on two widely-used benchmarks.

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