Network layout method and system based on segmentation drawing method and medium

Abstract

The invention provides a network layout method and system based on a segmentation drawing method and a medium. The network layout method comprises the following steps: a graph segmentation step: segmenting a whole graph by using a heuristic algorithm according to original data to obtain a plurality of sub-graphs; an inter-block layout step: generating an inter-block layout of the sub-graph based on the force guidance model of the graph layout according to the segmentation result; a sub-graph layout step: respectively laying out the sub-graphs by using the force guidance model to obtain an optimal sub-graph layout; a splicing step: splicing the sub-images according to the inter-block layout of the sub-images to obtain an initial finished image; and an adjustment step: adjusting the layout of initial mapping according to the force guidance model to obtain an optimal full-graph layout. According to the method, the super-large-scale network is laid out based on the segmentation drawing method, so that the data volume capable of being processed by a network layout algorithm is greatly improved, and the million-order barrier of a network visualization algorithm is broken through.

Description

technical field [0001] The present invention relates to the technical field of data network, in particular to a method, system and medium for network layout based on segmentation drawing method. Background technique [0002] With the advancement of technology and the development of science, the volume of academic network data is growing rapidly, and big data analysis and visualization are gradually changing our lives. In the field of network visualization, network layout algorithms occupy an important position. The academic network is abstract, and we cannot see the structure and aggregation of data from the excel table. The layout of the academic network can better solve this problem. However, as the volume of academic network data increases, the layout of data becomes more and more difficult. Most of the current network layout algorithms are still unable to handle very large volumes of data. [0003] Existing network visualization algorithms such as Force Atlas, Frucht...

AI Technical Summary

Problems solved by technology

When the number of nodes in the network exceeds this upper limit, the efficiency of the layout algorithm drops sharply

However, the number of nodes in the academic network is usually on the order of millions or even higher. The huge difference between the performance bottleneck of the algorithm and the actual demand has caused a huge obstacle to revealing the spatial structure of the actual academic big data, and faces many severe technical challenges.

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