Continuous matching of evolving patterns over dynamic graph data

Abstract Nowadays, the scale of various graphs soars rapidly, which imposes a serious challenge to develop processing and analytic algorithms. Among them, graph pattern matching is one most primitive tasks that find wide spectrum applications, performance yet often affected by size dynamicity graphs. In order handle large dynamic graphs, incremental proposed avoid re-computing matches patterns over entire data graph, hence reducing time improving overall execution performance. Due complexity problem, little work has been reported so far solve them only problem under scenario varying alone. this article, we are devoted more complicated but very practical continuous evolving , investigation presents novel algorithm for continuously along with changes both graph. Specifically, propose concise representation partial solutions, can help speed up subsequent process. enable updates an maintenance strategy, efficiently maintain intermediate results. Moreover, conceive effective model estimating step-wise cost evaluation drive Extensive experiments verify superiority .