Visual Recommendations for Network Navigation

Tarik Crnovrsanin²    Isaac Liao ²    Yingcai Wu¹    Kwan-Liu Ma²
This project was conducted when Yingcai Wu worked in UC Davis.
¹Microsoft Research Asia      ²University of California, Davis

The user interface. The left panel is an overview of the graph. The center panel is our recommendation system with suggestion-aware layout. An ontology graph of all node properties is in the upper right. The bottom right panel allows users to restrict displayed nodes to specified search terms.

Understanding large, complex networks is important for many critical tasks, including decision making, process optimization, and threat detection. Existing network analysis tools often lack intuitive interfaces to support the exploration of large scale data. We present a visual recommendation system to help guide users during navigation of network data. Collaborative filtering, similarity metrics, and relative importance are used to generate recommendations of potentially significant nodes for users to explore. In addition, graph layout and node visibility are adjusted in real-time to accommodate recommendation display and to reduce visual clutter. Case studies are presented to show how our design can improve network exploration.

@article {YWu2011b,
author = {Tarik Crnovrsanin and Isaac Liao and Yingcai Wu and Kwan-Liu Ma},
title = {Visual Recommendations for Network Navigation} ,
journal = {Computer Graphics Forum},
year = {2011},
volume = {30},
number = {3},
pages = {1081--1090 }
}