TRIC: A Triples Corrupter for Knowledge Graphs
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-43458-7_22
Reference8 articles.
1. Jia, S., Xiang, Y., Chen, X., Wang, K.: Triple trustworthiness measurement for knowledge graph. In: The World Wide Web Conference, pp. 2865–2871 (2019)
2. Paulheim, H.: Knowledge graph refinement: a survey of approaches and evaluation methods. Semant. Web 8(3), 489–508 (2017)
3. Lecture Notes in Computer Science;T Pellissier Tanon,2020
4. Senaratne, A., Christen, P., Williams, G., Omran, P.G.: Unsupervised identification of abnormal nodes and edges in graphs. JDIQ 15(1), 1–37 (2022)
5. Senaratne, A., Omran, P.G., Williams, G., Christen, P.: Unsupervised anomaly detection in knowledge graphs. In: IJCKG, pp. 161–165 (2021)
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