dNNG: Quality metrics and layout for neighbourhood faithfulness
Quan Hoang Nguyen, Seok‐Hee Hong, Peter Eades · 2017
This paper introduces a new kind of geometric graph, called the degree-sensitive neighbourhood graph (dNNG), for a more precise modelling of neighbourhoods. Based on dNNG, we define better shape-based metrics and then propose a neighbourhood-driven force-directed algorithm, called NEFO, for neighbourhood faithfulness. Our evaluation on both real-world and randomly generated graphs shows that the dNNG gives more effective shape-based measures when compared to existing geometric graphs. The NEFO algorithm is shown to be effective for improving neighbourhood faithfulness of graph drawings.