Title
Inverse Markov Process Based Constrained Dynamic Graph Layout
Abstract
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.
Year
DOI
Venue
2021
10.1007/s11390-021-9910-5
JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY
Keywords
DocType
Volume
graph drawing, data stream, dynamic graph layout
Journal
36
Issue
ISSN
Citations 
3
1000-9000
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Shiying Sheng142.12
Shengtao Chen200.34
Xiaoju Dong365.18
Chunyuan Wu401.69
Xiaoru Yuan5115770.28