Graph pattern matching is an important method for efficient query on graph data,which has wide application prospects,such asknowledge discovery,intelligent question answering,social network analysis, and so on. Most of the existing researches are generallybased on static graph data. However,many graph data with time information in real world belong to temporal?graphs. Aiming at graphpattern matching in temporal graphs,a temporal priority constrained graph pattern strong simulation matching method is proposed. It introduces the constraints?
of time orders into the pattern graph matching as while matching the graph topology of pattern graphs,namely,itconsiders the temporal priorities of different temporal edges in temporal?
graphs. Meanwhile,redundant vertex filtering rules are set tonarrow the search scope and optimize the queue of time order, so as to prune the graph in advance and reduce the computationalcomplexity. Moreover,the temporal edge closeness is proposed to evaluate the algorithm＇ s performance by the filtering effects ontemporal edges. Experiments results on three temporal datasets have shown that the proposed method can effectively filter out the errormatching results compared with the traditional strong simulation algorithm, and also has satisfactory performance on data graphs ofdifferent scales.