32 citations · 34 across the 5 of their papers we have counts for
Showing 2023Show all
2 papers · 1 filter
cs.HC2023
RekomGNN: Visualizing, Contextualizing and Evaluating Graph Neural Networks Recommendations
Camelia D. Brumar, Gabriel Appleby, Jen Rogers +4
Content recommendation tasks increasingly use Graph Neural Networks, but it remains challenging for machine learning experts to assess the quality of their outputs. Visualization s…
cs.HC2023★ 32 cited
Knowledge Graphs in Practice: Characterizing their Users, Challenges, and Visualization Opportunities
Harry Li, Gabriel Appleby, Camelia Daniela Brumar +2
This study presents insights from interviews with nineteen Knowledge Graph (KG) practitioners who work in both enterprise and academic settings on a wide variety of use cases. Thro…