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
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.