Research On Recommendation Algorithm And Rule Extraction Based On Variable Precision Operators Under Network Formal Decision Context

Concept cognition and knowledge discovery under network data are hot research topics in the field of network data analysis.It is very pioneering and meaningful to combine the formal concept analysis theory with the complex network analysis method,give full play to the advantages of their respective theories,and carry out the corresponding theoretical cross research and application research.In this paper,based on the network formal decision context,combined with the topological characteristics of complex networks and two types of operators in formal concept analysis,the recommendation system algorithm and the algorithm of infectious disease diagnosis rule extraction are studied,and the effectiveness of the proposed algorithm is illustrated through comparative experiments.The main work of this paper includes the following two aspects:1.Research on neighborhood recommendation algorithm based on causal force under variable-precision common operator.Firstly,the network formal decision context is proposed,which unifies the formal decision context and complex network analysis under one data framework.Then,the variable precision common operator is defined under the network formal decision context to obtain the variable precision weakenconcepts,and the traditional formal concept is weakened to make it closer to practical application.Secondly,combined with the theory of causal force and recommendation system,a neighborhood recommendation algorithm based on causal force under variable precision common operator is proposed.Finally,based on the Movie Lens dataset and the Filmtrust dataset,experimental comparisons are carried out,and the experiments show that the algorithm proposed in this paper is obviously better than others in the aspects of accuracy,recall,F1 and running time.2.Network rule extraction algorithm based on variable precision possible operator under the network formal decision context.Firstly,the practical significance of possible operators and necessary operators in the diagnosis of infectious diseases is analyzed on the basis of the network formal decision context,and the variable precision possible operators and their related properties are studied in the network formal decision context.Then,the variable precision weaken-concepts are defined,and the weak concept logic of variable precision network is proposed,which lays a theoretical foundation for the extraction of network rules later.Finally,a network rule extraction algorithm based on variable precision possible operator is proposed,and the proposed algorithm is experimentally compared with the common classification algorithm in machine learning based on the UCI dataset,and the experimental results show that the proposed rule extraction algorithm is effective.