Knowledge graph embedding methods for entity alignment: experimental review

• Published in: Data mining and knowledge discovery Vol. 37; no. 5; pp. 2070 - 2137
• Main Authors: Fanourakis, Nikolaos, Efthymiou, Vasilis, Kotzinos, Dimitris, Christophides, Vassilis
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.09.2023; Springer Nature B.V; Springer
• Subjects: Alignment; Artificial Intelligence; Chemistry and Earth Sciences; Computer Science; Data Mining and Knowledge Discovery; Effectiveness; Efficiency; Embedding; Graph theory; Graphs; Information Storage and Retrieval; Knowledge representation; Names; Performance measurement; Physics; Statistical methods; Statistics for Engineering; Entity alignment; Knowledge graph embeddings; Knowledge graphs

In recent years, we have witnessed the proliferation of knowledge graphs (KG) in various domains, aiming to support applications like question answering, recommendations, etc. A frequent task when integrating knowledge from different KGs is to find which subgraphs refer to the same real-world entity...