Inverse Markov Process Based Constrained Dynamic Graph Layout
| Autor: | Xiaoru Yuan, Chunyuan Wu, Shiying Sheng, Xiaoju Dong, Sheng-Tao Chen |
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| Rok vydání: | 2021 |
| Předmět: |
Sequence
Heuristic Computer science Graph Layout Markov process Function (mathematics) Computer Science Applications Theoretical Computer Science law.invention symbols.namesake Computational Theory and Mathematics PageRank Hardware and Architecture law Graph drawing symbols Node (circuits) Algorithm Software |
| Zdroj: | Journal of Computer Science and Technology. 36:707-718 |
| ISSN: | 1860-4749 1000-9000 |
| DOI: | 10.1007/s11390-021-9910-5 |
| Popis: | In online dynamic graph drawing, constraints over nodes and node pairs help preserve a coherent mental map in a sequence of graphs. Defining the constraints is challenging due to the requirements of both preserving mental map and satisfying the visual aesthetics of a graph layout. Most existing algorithms basically depend on local changes but fail to do proper evaluations on the global propagation when setting constraints. To solve this problem, we introduce a heuristic model derived from PageRank which simulates the node movement as an inverse Markov process hence to give a global analysis of the layout's change, according to which different constraints can be set. These constraints, along with stress function, generate layouts maintaining spatial positions and shapes of relatively stable substructures between adjacent graphs. Experiments demonstrate that our method preserves both structure and position similarity to help users track graph changes visually. |
| Databáze: | OpenAIRE |
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