A Novel Framework for Fuzzy Knowledge Graph Integration from Multiple Data Sources: Case Study in Healthcare
Tác giả
Tài liệu tham khảo
[1] Merkert, J., Mueller, M., Hubl M.: A survey of the application of machine learning in decision support systems (2015)
[2] Pombo, N., Araújo, P., Viana, J.: Knowledge discovery in clinical decision support systems for pain management: a systematic review. Artif. Intell. Med. 60(1), 1–11 (2014)
[3] Singhal, A.: Introducing the knowledge graph: things, not strings. Official google blog 5.16 (2012). https://blog.google/products/search/introducing-knowledge-graph-things-not/
[4] Nicholson, D.N., Greene, C.S.: Constructing knowledge graphs and their biomedical applications. Comput. Struct. Biotechnol. J. 18, 1414–1428 (2020)
[5] Lan, L.T.H., et al.: A new complex fuzzy inference system with fuzzy knowledge graph and extensions in decision making. IEEE Access 8, 164899–164921 (2020)
[6] Long, C.K., Van Hai, P., Tuan, T.M., Lan, L.T.H., Chuan, P.M., Son, L.H.: A novel fuzzy knowledge graph pairs approach in decision making. Multimedia Tools Appl. 81(18), 26505–26534 (2022)
[7] Long, C.K., Hai, P.V., Tuan, T.M., et al.: A novel Q-learning-based FKG-Pairs approach for extreme cases in decision making. Eng. Appl. Artif. Intell., 120 (2023), ISSN 0952–1976, https://doi.org/10.1016/j.engappai.2023.105920
[8] Yang, P., et al.: LMKG: a large-scale and multi-source medical knowledge graph for intelligent medicine applications. Knowl.-Based Syst., 111323 (2023)
[9] Yan, C., Fang, X., Huang, X., Guo, C., Wu, J.: A solution and practice for combining multi-source heterogeneous data to construct enterprise knowledge graph. Front. Big Data, 6 (2023)
[10] Finlayson, A., Martin, J.: Introduction: Rhetoric and the British way of politics. Rhetoric in British politics and society. London: Palgrave Macmillan UK, pp. 1–13 (2014)
[11] Zhou, X., Menche, J., Barabási, A.L., Sharma, A.: Human symptoms–disease network. Nat. Commun. 5(1), 4212 (2014)
[12] Li, L., et al.: Real-world data medical knowledge graph: construction and applications. Artif. Intell. Med. 103, 101817 (2020)
[13] Weng, H., Chen, J., Ou, A., Lao, Y.: Leveraging representation learning for the construction and application of a knowledge graph for traditional Chinese medicine: framework development study. JMIR Med. Inform. 10(9), e38414 (2022)
[14] Cheng, B., Zhang, J., Liu, H., Cai, M., Wang, Y.: Research on medical knowledge graph for stroke. J. Healthc. Eng., 2021 (2021)
[15] Ernst, P., Siu, A., Weikum, G.: Knowlife: a versatile approach for constructing a large knowledge graph for biomedical sciences. BMC Bioinform. 16, 1–13 (2015)
[16] Sun, P., Gu, L.: Fuzzy knowledge graph system for artificial intelligence-based smart education. J. Intell. Fuzzy Syst. 40(2), 2929–2940 (2021)
[17] Yang, E., Hao, F., Gao, J., Park, D.S.: Entity summarization in fuzzy knowledge graph based on fuzzy concept analysis. In: Advanced Multimedia and Ubiquitous Engineering: MUE-FutureTech 2020, pp. 19–24. Springer, Singapore (2021)