WebOct 1, 2024 · Abstract. Entity alignment (EA) aims to find equivalent entities in different knowledge graphs (KGs). Current EA approaches suffer from scalability issues, limiting their usage in real-world EA ... WebEntity alignment (EA) is to discover equivalent entities in knowledge graphs (KGs), which bridges heterogeneous sources of information and facilitates the integration of …

Degree-Aware Alignment for Entities in Tail - typeset.io

WebEntity alignment (EA) is to discover equivalent entities in knowledge graphs (KGs), which bridges heterogeneous sources of information and facilitates the integration of … WebJan 11, 2024 · Embedding-based entity alignment approaches encode entities in a continuous embedding space where entities are aligned based on the similarity of learned embeddings. However, there exists ambiguity and uncertainty in entity alignment caused by single alignment metric. In this paper, a fuzzy entity alignment method FuzzyEA is … property to rent in west lothian scotland

Degree aware based adversarial graph convolutional networks for entity …

WebMay 28, 2024 · To address the above challenge and mitigate the impact of degree difference on entity alignment task, a novel degree aware adversarial graph … Webrelations and degree of entities. The output of the degree-aware random walk is then sent to our heterogeneous sequence learning model to learn embeddings. After sequence learning, we get alignment results via calculating embedding sim-ilarities. Our main contributions in this paper are summarized as follows: WebDec 15, 2024 · Moreover, an iterative framework is designed to leverage the positive interactions between the entity alignment and the relation alignment in a semi-supervised manner. Experimental results on three real-world datasets demonstrate that the proposed model RNM performs better than state-of-the-art methods. property to rent in weston coyney