Research On Recognition Of Vital Nodes In Temporal Bipartite Networks

In recent years,the leapfrog development of network science has brought us a new perspective to the real world.Many of the intricate relationships in the real world can be abstracted into networks that contain only simple elements and use the theory of network science to quantitatively describe and analyze the nature of these systems.In the field of network science,it is of great practical significance to identify and research important nodes for the robustness and reliability of complex networks.Unlike the majority of nodes in the network,the number of important nodes in the network is small,but it is of vital importance to the structure or function of the network.Network-based important node identification have a close relationship with network control,synchronization,propagation,prediction and so on.As the important nodes of the network identify significant theoretical research significance and extensive practical application value,the research on important node recognition methods has been a hot research direction in the field of network science.Based on the time dimension,we study the important nodes in complex networks.The main contents of this paper are as follows:(1)In this paper,the algorithms of IR,CR,IARR,BiHITS and QR are introduced in detail,and the advantages and disadvantages of each method are compared.(2)Research on the ranking algorithm based on time dimension,and put forward two indicators of quantitative ranking from time dimension: novelty and balance.And in the follow-up experiments found that the classic important node recognition algorithm there is the problem of ranking the old node.(3)An important node recognition algorithm based on H-index is proposed for the non-weight dichotomy network.The algorithm takes into account the node weight and time evolution process,which is better than the traditional method and makes the recognition accuracy of important nodes higher.In two real networks to test and found that the new algorithm found that the important nodes are more novel.(4)A BiHITS improved algorithm based on time balance is proposed for weighted dichotomous networks.The algorithm adds a rebalancing process based on the general iterative algorithm,so that the objects of different time groups can be compared together.The algorithm preserves the robustness of the original algorithm and greatly improves the time balance of the algorithm.The experimental results show that the new algorithm improves the accuracy of the identification of new excellent merchandise.