Network graph data extraction method based on attention learning

Abstract

The invention discloses a network graph data extraction method based on attention learning. The method is characterized by comprising the following steps: extracting character data in a graph by adopting a character extraction deep neural network, extracting pixel characteristics of a visual graph of a network graph by adopting a semantic segmentation network having an attention module, and calculating data of a node and a connection relationship, so that a data structure of an original network graph can be recovered. Compared with the prior art, the method has the advantages that: the problem of data mining of advanced visual coding of network graphs is well solved; the problem of connecting line recognition is solved through an attention mechanism, the robustness of a model is improved; data extraction can be carried out on bitmaps of network graph visualization charts in various practical application scenes such as data conversion, visualization design style switching, and intellectual property protection, and the method has high practical value and good development prospects.

Description

technical field [0001] The invention relates to the technical field of graph data extraction, in particular to a method for extracting original data of network graphs based on attention learning. Background technique [0002] Data visualization images can help people get data characteristics faster, and most charts are stored in the form of bitmap images and published on various media. Obtaining their raw data is a complex task, and recovering the raw data of graphs has become an important research because its development directly contributes to the field of human-computer interaction. [0003] Network diagrams refer to relationship diagrams with text information and different styles, including mind maps, modeling diagrams, flowcharts, etc. They are high-level visual codes that are easy for humans to understand but difficult for machines to decode. Studies have shown that there are some methods to solve the problem of obtaining original data, but these methods are only suit...

AI Technical Summary

Problems solved by technology

Studies have shown that there are some methods to solve the problem of obtaining original data, but these methods are only suitable for some simple charts, such as pie charts, bar charts and line charts. It is difficult to identify connecting lines, and there is also a problem of matching text and graphics

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