Semantic Zooming Approach to Semantic Link Network Visualization

被引:0
|
作者
Litovkin, Dmitry [1 ]
Anikin, Anton [1 ]
Kultsova, Marina [1 ]
机构
[1] Volgograd State Tech Univ, Volgograd, Russia
关键词
Semantic web; Semantic link network; WHAT-knowledge; Semantic zooming; KNOWLEDGE; CLASSIFICATION; MAPS;
D O I
10.1007/978-3-030-29750-3_7
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In the paper, we described a semantic zooming approach to the visualization of special kind structures - semantic link networks (SLN), represented as a visual graph. The proposed approach allows decreasing semantic noise in SLN overview and navigation and also simplifies the process of understanding the domain studied with SLN by means of semantic zooming. We proposed priori importance levels of SLN items and semantic zooming scale to visualize the SLN with different details level. We designed an interactive SLN visualization process including the following SLN transformations: filtering SLN items, context collapse and expansion for SLN item, and changing the details in the visualized object representation in the geometric SLN graph. The transformation algorithms were developed, and also examples of SNL semantic zooming were described in details in the paper.
引用
收藏
页码:81 / 95
页数:15
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