Pienta Robert, Tamersoy Acar, Tong Hanghang, Endert Alex, Chau Duen Horng
Georgia Tech.
Arizona State University.
IUI. 2015 Mar-Apr;2015(Companion):61-64. doi: 10.1145/2732158.2732192.
Given the explosive growth of modern graph data, new methods are needed that allow for the querying of complex graph structures without the need of a complicated querying languages; in short, is desirable. We describe our work towards achieving our overall research goal of designing and developing an interactive querying system for large network data. We focus on three critical aspects: scalable data mining algorithms, graph visualization, and interaction design. We have already completed an approximate subgraph matching system called MAGE in our previous work that fulfills the algorithmic foundation allowing us to query a graph with hundreds of millions of edges. Our preliminary work on visual graph querying, Graphite, was the first step in the process to making an interactive graph querying system. We are in the process of designing the graph visualization and robust interaction needed to make truly interactive graph querying a reality.
鉴于现代图数据的爆炸式增长，需要新的方法来实现对复杂图结构的查询，而无需使用复杂的查询语言；简而言之，这是可取的。我们描述了为实现设计和开发大型网络数据交互式查询系统这一总体研究目标所做的工作。我们专注于三个关键方面：可扩展的数据挖掘算法、图可视化和交互设计。在我们之前的工作中，已经完成了一个名为MAGE的近似子图匹配系统，该系统奠定了算法基础，使我们能够查询具有数亿条边的图。我们在可视化图查询方面的初步工作Graphite，是迈向构建交互式图查询系统过程中的第一步。我们正在设计使真正的交互式图查询成为现实所需的图可视化和强大交互。
