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Pattern Recognition and Artificial Intelligence  2024, Vol. 37 Issue (5): 469-478    DOI: 10.16451/j.cnki.issn1003-6059.202405008
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Knowledge Discovery and Rule Extraction Based on Heterogeneous Network Linguistic Formal Context
SHA Liwei1, YANG Zheng1, LIU Hongping2, ZOU Li1
1. School of Computer Science and Technology, Shandong Jianzhu University, Jinan 250101;
2. School of Science, Shandong Jianzhu University, Jinan 250101

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Abstract  One of the research hotspots is how to handle data with complex relationships under the uncertainty environment. The network formal context combines complex network analysis and formal concept analysis to provide an effective mathematical tool for knowledge discovery of complex relational data. In this paper, the heterogeneous network linguistic formal context is firstly proposed based on the heterogeneity of network structure. The heterogeneous network contains a subjective network given by experts and an objective network mined by the features of objects. Then, global and local heterogeneous network language concepts are obtained by considering the connectivity of the network, and the algorithms for global and local connectivity knowledge discovery in heterogeneous networks are provided. Finally, an association rule extraction model is constructed based on the heterogeneous network linguistic formal context, and the rationality and effectiveness of knowledge discovery and rule extraction are verified by examples.
Key wordsFormal Concept Analysis      Heterogeneous Network      Fuzzy Clustering      Knowledge Disco-very      Rule Extraction     
Received: 07 April 2024     
ZTFLH: TP18  
Fund:National Natural Science Foundation of China(No.62176142,62177031), Natural Science Foundation of Shandong Province(No.ZR2021MF099,ZR2022MF334)
Corresponding Authors: ZOU Li, Ph.D., professor. Her research interests include intelligent information processing, non-classical logic and uncertainty reasoning.   
About author:: SHA Liwei, Master student. His research interests include intelligent information processing, non-classical logic and uncertainty reasoning. YANG Zheng, Master student. His research interests include intelligent information processing, non-classical logic and uncertainty reasoning. LIU Hongping, Ph.D., associate profe-ssor. Her research interests include fuzzy topology, Domain theory and intelligent information processing.
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SHA Liwei
YANG Zheng
LIU Hongping
ZOU Li
Cite this article:   
SHA Liwei,YANG Zheng,LIU Hongping等. Knowledge Discovery and Rule Extraction Based on Heterogeneous Network Linguistic Formal Context[J]. Pattern Recognition and Artificial Intelligence, 2024, 37(5): 469-478.
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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.202405008      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2024/V37/I5/469
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