2017/09/20 by Huiju Wang, Wang, Huiju, Zhengkui Wang +8
Computer Science · Physics and Astronomy · #Complex Network Analysis Techniques #Data Visualization and Analytics #Databases (cs.DB) #FOS: Computer and information sciences #Graph Theory and Algorithms #Social and Information Networks (cs.SI)
paper · pdf · doi:10.48550/arxiv.1709.06745
openalex publication_date 2017/09/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Graphs have been widely used to model different information networks, such as the Web, biological networks and social networks (e.g. Twitter). Due to the size and complexity of these graphs, how to explore and utilize these graphs has become a very challenging problem. In this paper, we propose, VCExplorer, a new interactive graph exploration framework that integrates the strengths of graph visualization and graph summarization. Unlike existing graph visualization tools where vertices of a graph may be clustered into a smaller collection of super/virtual vertices, VCExplorer displays a small number of actual source graph vertices (called hubs) and summaries of the information between these vertices. We refer to such a graph as a HA-graph (Hub-based Aggregation Graph). This allows users to appreciate the relationship between the hubs, rather than super/virtual vertices. Users can navigate through the HA- graph by "drilling down" into the summaries between hubs to display more hubs. We illustrate how the graph aggregation techniques can be integrated into the exploring framework as the consolidated information to users. In addition, we propose efficient graph aggregation algorithms over multiple subgraphs via computation sharing. Extensive experimental evaluations have been conducted using both real and synthetic datasets and the results indicate the effectiveness and efficiency of VCExplorer for exploration.