Interactive Visual Pattern

Interactive visual pattern discovery aims to leverage human intuition to identify meaningful patterns within complex datasets, particularly graphs and high-dimensional data. Current research focuses on developing algorithms, such as graph neural networks and novel 3D visualization techniques (e.g., General Line Coordinates), that enable efficient and interpretable pattern exploration. This approach enhances the understanding of learned models, facilitates more effective data analysis by non-experts, and improves the design of pattern mining systems through iterative user feedback and refinement. The ultimate goal is to bridge the gap between complex data analysis and human comprehension, leading to more robust and insightful discoveries across various scientific and practical domains.