Method for visualizing layout optimization of graph data based on force guiding algorithm

Abstract

The invention relates to a method for visualizing layout optimization of graph data based on a force guiding algorithm. The method, to optimize the visual layout of the graph data, in the loop iteration process of the force guiding algorithm, adds the following processing step that in the case of node adhesion, the position of the pop-up of nodes and the direction of the pop-up of the nodes are given by a random function, so that the adhesive nodes are separated from each other by a certain distance, and the attracting force and the repulsive force in the case of node adhesion can be calculated. Further, the method adopts a gradient setting for parameter delta values in the displacement calculation of the force guiding algorithm, so that the visualization process of the graph data reducesthe shock and quickly converges. The method can solve the above problems in the basic force guiding layout algorithm and improves the layout efficiency of the algorithm while optimizing the layout effect of the algorithm.

Description

technical field [0001] The invention belongs to the technical fields of information understanding and processing, big data processing, multi-source data association analysis, graph data visualization and visualization analysis, and specifically relates to a graph data visualization layout optimization method based on a force-guided algorithm. Background technique [0002] The era of big data has brought people unprecedented amounts of information. Information Visualization is a method and technology that can intuitively convey abstract information, support information exploration and verify assumptions, and help people better understand information and think. Graphs are one of the important methods for representing relational data in information visualization. Graph methods have important applications in social network analysis, sequence analysis, search services and other fields. [0003] The graph method can quickly present a large amount of information in relational data...

AI Technical Summary

Problems solved by technology

The selection of the delta value is related to the displacement of the node after the force is applied. If the delta is selected too large, when the length of the spring is much greater than the original length of the spring, the spring will be greatly attracted. In the state of oscillation, it is difficult to move to a balanced position, so that the layout has been unable to converge; but if the delta is selected to be small, the movement displacement of each node will be relatively small, and it takes many iterations to make the layout converge, so that the algorithm reduced performance of

The existing algorithm can only select a specific delta value, so that the selection of the delta value always has the above problems, so that in another iteration, the nodes do not move as much as possible towards the final stable state

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