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A transform-based visual analysis method and system for relational graphs

An analysis method and a technology of association diagrams, applied in the field of information visualization, can solve problems such as inability to realize description and exploration at the same time, and achieve the effect of reducing visual complexity

Active Publication Date: 2020-07-10
BEIJING TECHNOLOGY AND BUSINESS UNIVERSITY
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Problems solved by technology

[0007] Existing visualization methods are often unable to realize the description and exploration of complex associations, highlight key objects, and comprehensively display associated information when solving the visual analysis of associated data.

Method used

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  • A transform-based visual analysis method and system for relational graphs
  • A transform-based visual analysis method and system for relational graphs
  • A transform-based visual analysis method and system for relational graphs

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Embodiment Construction

[0068] The following will further describe the present invention through examples in conjunction with the accompanying drawings, but the scope of the present invention is not limited in any way.

[0069] The present invention provides a transform-based visual analysis method, system and application of an association graph, which displays complex associations in data sets from the perspectives of association description and exploration (such as figure 2shown), using force-guided layout methods (node-link graphs), graph simplification techniques (K-means clustering, fisheye transformation techniques based on graph topology, graph filtering and edge binding techniques) and graph visualization The interaction design (focus + context technology, pan and zoom technology, global + detail technology and interactive dynamic filtering). The method of the invention can solve the problem of visual confusion easily caused by edge intersections when expressing complex associations, highlig...

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Abstract

The present invention discloses a transformation-based visual analysis method, system and application of an association graph, through association description and association exploration in the association graph TransGraph two views display complex associations in a data set, using a force-guided layout method, diagram Simplify technology and interactive design in graph visualization, realize visual analysis of data association information, solve the problem of visual confusion caused by edge intersections when expressing complex associations, highlight key regulatory objects, and comprehensively display association information. Therefore, it can effectively assist analysts in making decisions. The visual analysis method can be applied to the visual analysis of the pesticide residue detection result data set, and a visual analysis system for the association of pesticide residue data realized by the visual analysis method is provided.

Description

technical field [0001] The invention belongs to the field of information visualization, and relates to a data visual analysis method, in particular to a transform-based visual analysis method of an association graph and a system thereof. Background technique [0002] Correlation has always been an important research object of data analysis, and exists in various fields in the real world. Taking pesticide residue data as an example, it consists of two disjoint sets of pesticides and agricultural products. At the same time, the relationship between pesticides and agricultural products There is a residual relationship between them. Graphs are a common mathematical method used to model relationships, which can effectively summarize the connections between things at a high level. From a visualization perspective, graph visualization is also an important branch of the field of information visualization. Also known as association network, network or association graph, it is the co...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/26G06K9/62
CPCG06F16/26G06F18/23213
Inventor 陈谊杜晓敏管泽礼
Owner BEIJING TECHNOLOGY AND BUSINESS UNIVERSITY
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