Adaptive Algorithms for Graph Views and View Transitions (B06*)

• Subject Area: Theoretical Computer Science
• Term: since 2019
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 251654672

This project aims at visualizing complex graph data in an adaptive manner, guided by quality aspects and user input. The new focus is on consistent view ensemble creation for high-dimensional input data, as e.g. derived from evolving neural networks. Our main idea is to use, extend, and (for the first time) combine the notions of regret (which is an established measure for subset quality based on user preference models) and dimensionality reduction to design scalable graph drawing and view selection algorithms that come with quality guarantees.

• DFG Programme: CRC/Transregios
• Subproject of: TRR 161: Quantitative Methods for Visual Computing
• Applicant Institution: Universität Stuttgart
• Project Head: Professorin Dr. Sabine Storandt