中文摘要：

提出了一种数据流预测算法Predictor.该算法为每个待匹配的一般形式的情节规则分别使用了一个自动机,通过单遍扫描数据流来同时跟踪这些自动机的状态变迁,以搜索每个规则前件最近的最小且非重叠发生.这样不仅将无界的数据流映射到有限的状态空间,而且避免了对情节规则的过于匹配.另外,算法预测的结果是未来多个情节的发生区间和发生概率.理论分析和实验评估表明,Predictor具有较高的预测效率和预测精度.

英文摘要：

This paper proposes an algorithm called Predictor.This algorithm uses an automaton per matched episode rule with general form.With the aim of finding the latest minimal and non-overlapping occurrence of all antecedents,Predictor simultaneously tracks the state transition of each automaton by a single scanning of data stream,which can not only map the boundless streaming data into the finite state space but also avoid over-matching episode rules.In addition,the results of Predictor contain the occurring intervals and occurring probabilities of future episodes.Theoretical analysis and experimental evaluation demonstrate Predictor has higher prediction efficiency and prediction precision.