基于变精度可能算子的网络概念认知

网络上的概念认知是网络数据分析领域的一个重要方向。从形式概念分析中的必然算子、可能算子出发,提出变精度可能算子,表明经典可能算子是变精度可能算子的特殊情形;进一步,对可能算子的性质进行研究,并解释它们在传染病网络研究中的意义;接着,根据变精度可能算子提出两种网络广义概念及其上下近似与边界,通过实例说明基于变精度可能算子的上下近似和边界在网络概念认知中具有更丰富的语义;然后,结合复杂网络分析中的网络特征值方法,定义网络弱概念,并提出基于变精度可能算子的网络弱概念获取方法;最后,利用文中算法在UCI数据集上进行测试,结果证实了变精度可能算子在网络概念认知中的优势。

Cognition of network concepts based on variable precision possibility operator

Concept cognition in a network is an important direction in the field of network data analysis. Starting from the necessity operator and possibility operator in formal concept analysis, this paper puts forward variable precision possibility operator, and illustrates that the classical possibility operators are special cases of the variable precision possibility operators. Furthermore, some properties of the possibility operators are studied, and their significances in the study of infectious disease networks are explained. Then, based on the variable precision possibility operators, two generalized network concepts and their upper approximations, lower approximations and boundary regions are proposed, and the upper and lower approximations and their boundary regions under variable precision possibility operators are illustrated to have much richer semantics through an example. After that, combined with the network eigenvalue method in complex network analysis, the network weak concepts are defined, and a network weak concept acquisition method based on variable precision possibility operator is presented. Finally, our algorithm is used to conduct some experiments on the UCI database, and the obtained results show that variable-precision possibility operators have advantages in network concept cognition.