Parallelization critical node discovery method for postal delivery data

Abstract

The present invention relates to a parallelization critical node discovery method for postal delivery data. The method comprises the following steps: step S1: acquiring node activity according to the total number of sending and receiving times of each node in a set time in the postal delivery data, and taking the node activity as the own weight value of the node; step S2: acquiring the weight values of edges of each node pair according to the interaction frequency and shared neighbor number metric indexes of each node pair in the set time in the postal delivery data, and defining a network formed by the postal delivery data as a directed double-weighted network graph; and step S3: adding the own weight values of the nodes and the weight values of the edges of the node pairs on the basis of a PageRank algorithm, and excavating critical nodes in the directed double-weighted network graph in parallel. In contrast to the prior art, the parallelization critical node discovery method fully utilizes information in a logistics postal delivery network, reduces the loss of useful information, improves the accuracy of discovery of critical nodes in the network, and parallel operation is implemented at the same time, thereby greatly improving the efficiency and stability of critical node excavation.

Description

Technical field [0001] The invention relates to the technical field of social network analysis, in particular to a parallel key node discovery method oriented to forwarding data. Background technique [0002] Since the concept of "social network" was proposed by British scholars in 1920, researchers have never stopped studying social networks. Especially with the rapid development of biological information technology, network technology, communication technology, and social platforms, a huge complex social network has been formed between each individual in the social network. In social life, complex networks are closely related to our lives. The complex networks that we often come into contact with include: the Internet in the computer field, the World Wide Web, the communication network, the mail network, the Weibo network, the logistics delivery network in the logistics and the biomedical field The network of interactions between proteins. The key node is a kind of more impor...

AI Technical Summary

Problems solved by technology

However, most key node discovery algorithms only consider the weight of the edge, and few people take the weight of the node itself into account, which leads to ignoring a lot of useful information when mining key people in the network, which affects the key node discovery. accuracy

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