IEEE VIS 2024 Content: FishEye Watcher: a visual analytics system for knowledge graph bias detection

FishEye Watcher: a visual analytics system for knowledge graph bias detection

Tian Qiu - Fudan University, Shanghai, China

Yi Shan - Fudan University, Shanghai, China

Xueli Shu - Fudan University, Shanghai, China

Aolin Guo - Fudan University, Shanghai, China

Qianhui Li - Fudan University, Shanghai, China

Meng Guo - school of data science, Shanghai , China

Siming Chen - Fudan University, Shanghai, China

Room: Bayshore II

2024-10-13T12:30:00ZGMT-0600Change your timezone on the schedule page
2024-10-13T12:30:00Z
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Abstract

In this paper we present an interactive visualization system for solving IEEE VAST Challenge 2024 Mini-Challenge 1. Our system enables interactive exploration and mining of the knowledge graph, assists in identifying suspicious bias and provides corresponding evidence from multiple perspectives. For the convenience of user exploration, our system supports recording the exploration process and preservation of evidence. The illustrative case proves the effectiveness of our system.