TransFG: A Fine-Grained Model for Knowledge Graph Embedding
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-030-30952-7_45
Reference13 articles.
1. Wang, Q., Mao, Z., Wang, B., Guo, L.: Knowledge graph embedding: a survey of approaches and applications. IEEE Trans. Knowl. Data Eng. 29(12), 2724–2743 (2017)
2. Rosso, P., Yang, D., Cudré-Mauroux, P.: Knowledge graph embeddings. In: Sakr, S., Zomaya, A.Y. (eds.) Encyclopedia of Big Data Technologies. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-63962-8_284-1
3. Suchanek, F.M., Kasneci, G., Weikum, G.: Yago: a core of semantic knowledge. In: Proceedings of the 16th International Conference on World Wide Web, WWW 2007, pp. 697–706. ACM (2007). https://doi.org/10.1145/1242572.1242667
4. Lehmann, J., Isele, R., Jakob, M., et al.: DBpedia - a large-scale, multilingual knowledge base extracted from Wikipedia. Semant. Web 6(2), 167–195 (2015)
5. Lecture Notes in Computer Science;W Li,2018
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