FSM-Explorer: An Interactive Tool for Frequent Subgraph Pattern Mining From a Big Graph

Jalal Khalil, Da Yan, Lyuheng Yuan, Jiao Han, Saugat Adhikari, Cheng Long, Yang Zhou

Abstract: In this demonstration paper, we describe FSM-Explorer, an interactive tool that makes it easier for end-users to mine frequent subgraph patterns from a big graph $G$ , and to explore the subgraph instances in $G$ that match the patterns. FSM-Explorer not only supports the popular MNI support measure, but also the recently proposed Fraction-Score measure that is more accurate. Its backend engine is built on top of our recently developed T-FSM system that ensures high concurrency, bounded memory consumption, and effective load balancing. Using real-world data, we showcase how users can mine frequent subgraph patterns by parameter tuning in FSM-Explorer, and how they can conveniently examine the many matched instances in $G$ one batch at a time to improve productivity.