Big data knowledge graph visualization method and device

Abstract

Embodiments of the invention provide a big data knowledge graph visualization method and device. The method comprises the steps of obtaining to-be-visualized data; for the node data and the side datain the to-be-visualized data, based on a preset D3. Js library, obtaining formatted node data and formatted side data; based on a preset rendering mode, generating corresponding to-be-displayed nodesand to-be-displayed edges from the formatted node data and the formatted edge data; calculating a to-be-displayed position of each to-be-displayed node in the page and a to-be-displayed position of each to-be-displayed edge in the page in real time; and based on the to-be-displayed position of each to-be-displayed node in the page and the to-be-displayed position of each to-be-displayed edge in the page, rendering the to-be-displayed nodes and the to-be-displayed edges into the page to obtain a visual knowledge graph. According to the embodiment of the invention, the phenomenon of blockage canbe avoided in the process of displaying the visual knowledge graph.

Description

technical field [0001] The invention relates to the technical field of knowledge graph visualization, in particular to a method and device for visualizing a big data knowledge graph. Background technique [0002] With the development of big data, the relationship between various industries and big data is getting closer. Due to the characteristics of large-scale, heterogeneous and diverse data, and loose organizational structure, it poses challenges for people to effectively obtain information and knowledge. Therefore, the big data industry has introduced data visualization and knowledge graph technologies. Data visualization aims to convey and communicate information clearly and effectively by means of graphics. Data visualization represents each data item as a single graphic element, and a large number of data sets form a data image. At the same time, each attribute value of the data is represented in the form of multi-dimensional data. The data can be observed from diff...

AI Technical Summary

Problems solved by technology

[0004] However, in the existing SVG-based method for realizing big data knowledge map visualization, because SVG needs to generate a DOM (Document Object Model, Document Object Model) for each node and edge in the process of rendering nodes and edges to the page Node, and the mechanism of using SVG for rendering in browser pages determines that when displaying page animation, the position of each DOM node in the page needs to be redrawn and rearranged, and during the redrawing and rearrangement process The single-threaded calculation method is used to calculate the position of each DOM node, so that when the amount of data to be visualized is large, the data of nodes and edges in the page is large, for example, the number of nodes and edges reaches 2000 or 2000 In the above cases, the workload of redrawing and rearranging the DOM nodes is relatively large, which will cause the display to freeze during the process of rendering the nodes to the page.

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