Beyond Query: Exploratory Subgraph Discovery and Search System

在动态网络数据中探索共同工作的用户群在许多应用中是一个至关重要的挑战，例如在线教育。该项目旨在发现新的用户关系，并计算他们在连续时间段内的共同工作表现。设计了有效的子图探索模型，三种新型的子图搜索方案，并设计了一个友好的支持实时网络数据分析的探索性子图搜索系统。该项目的成功将为图数据挖掘的科学基础及其在数据工程领域的应用做出重大贡献，并有利于澳大利亚劳动力市场中人们的共同工作绩效。

Exploring co-working user groups in dynamic network data is a vital challenge in many applications, for example, in online education. This project aims to discover new relationships of users and compute their co-working performance in continuous time periods. The outcomes of the project are to design effective subgraph exploratory models, three novel types of subgraph search solutions, and devise a friendly exploratory subgraph search system for supporting the real-time network data analytics. The success of the project will make a significant contribution to the scientific foundation of graph data mining and its applications in data engineering domains, as well as benefiting co-working performance of people in Australian labor markets.