Method for quickly reconstructing propagation network structure

Abstract

The invention discloses a method for quickly reconstructing a propagation network structure, which comprises the following steps of: firstly, recording the association strength between each node Vi ina network and other nodes, namely each node in Lvi, and recording the association strength in a set MIvi, the Lvi being the remaining nodes except the Vi in the network; calculating the possibility degree that each node in the Lvi in the network is a Vi father node, and recording the possibility degree in a set PIvi; sorting the nodes in the Lvi in a descending order according to the associationstrength with the Vi to obtain a set SLvi, calculating the inflection point rate of each node in the SLvi, and recording the inflection point rates in a set BPvi; and finally, initializing a directedgraph G = {V, E}, sequentially considering each node Vi for n node sets V in the network, selecting p nodes with higher inflection point rates from BPvi to construct directed edges of the Vi, adding the directed edges into E, and returning G to a user. According to the method, the association degree and the influence relationship between the nodes can be quickly determined based on the collected infection state data, so that the latent influence relationship graph can be accurately deduced.

Description

technical field [0001] The invention relates to the technical field of information dissemination, in particular to a method for quickly reconfiguring a dissemination network structure. Background technique [0002] Advances in science and technology have made the process of information dissemination more convenient and frequent, leading to the formation of a complex information dissemination network. Obtaining the structure of the dissemination network can help intuitively understand these dissemination networks and understand the related dissemination process, so as to better promote Or prevent the future information dissemination process. For example, in the process of infectious disease transmission, after discovering the potential transmission network of infectious diseases, the disease prevention and control department can better mobilize epidemic prevention resources to prevent and control potential susceptible groups, so as to prevent the epidemic from worsening. Redu...

AI Technical Summary

Problems solved by technology

In many actual transmission processes, such as the process of disease transmission, the exact infection time information is often missing, resulting in a large limitation in the availability of reconstruction algorithms based on infection time information

However, node infection status data cannot directly reflect the influence relationship between nodes in the network, so the reconstruction algorithm based on node infection status generally has a high time complexity. Therefore, how to use the easily obtained infection status data to quickly reconstruct The structure of the communication network has important research significance and practical value. Therefore, a method for quickly reconstructing the structure of the communication network is proposed

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