GraphCharter: Combining browsing with query to explore large semantic graphs
Ying Tu, Han‐Wei Shen · 2013
Large scale semantic graphs such as social networks and knowledge graphs contain rich and useful information. However, due to combined challenges in scale, density, and heterogeneity, it is impractical for users to answer many interesting questions by visual inspection alone. This is because even a semantically simple question, such as which of my extended friends are also fans of my favorite band, can in fact require information from a non-trivial number of nodes to answer. In this paper, we propose a method that combines graph browsing with query to overcome the limitation of visual inspection. By using query as the main way for information discovery in graph exploration, our “query, expand, and query again” model enables users to probe beyond the visible part of the graph and only bring in the interesting nodes, leaving the view clutter-free. We have implemented a prototype called GraphCharter and demonstrated its effectiveness and usability in a case study and a user study on Freebase knowledge graph with millions of nodes and edges.