论文标题
将Shinohara的算法扩展到计算描述性（盎格鲁因）模式到子序列模式
Extending Shinohara's Algorithm for Computing Descriptive (Angluin-Style) Patterns to Subsequence Patterns
论文作者
论文摘要
在开创性工作中引入模式语言[Angluin，``找到一组字符串的模式''，JCSS 1980]恢复了归纳推理的经典模型（在极限，金色式学习中学习）。在[shinohara，``模式语言及其应用的多项式时间推断''，第七届IBM计算机科学数学基础的研讨会1982年]一种简单而优雅的算法，基于成员资格查询，计算一种对给定的输入串的描述性的模式，可以对输入串的示例进行描述（以及均可用来的策略，并且可以用来均应进行策略。 In this paper, we give a brief survey of the recent work [Kleest-Meißner et al., ``Discovering Event Queries from Traces: Laying Foundations for Subsequence-Queries with Wildcards and Gap-Size Constraints'', ICDT 2022], where the classical concepts of Angluin-style (descriptive) patterns and the respective Shinohara's algorithm are extended to a query class with复杂事件识别中的应用程序 - 数据库中的现代主题。
The introduction of pattern languages in the seminal work [Angluin, ``Finding Patterns Common to a Set of Strings'', JCSS 1980] has revived the classical model of inductive inference (learning in the limit, gold-style learning). In [Shinohara, ``Polynomial Time Inference of Pattern Languages and Its Application'', 7th IBM Symposium on Mathematical Foundations of Computer Science 1982] a simple and elegant algorithm has been introduced that, based on membership queries, computes a pattern that is descriptive for a given sample of input strings (and, consequently, can be employed in strategies for inductive inference). In this paper, we give a brief survey of the recent work [Kleest-Meißner et al., ``Discovering Event Queries from Traces: Laying Foundations for Subsequence-Queries with Wildcards and Gap-Size Constraints'', ICDT 2022], where the classical concepts of Angluin-style (descriptive) patterns and the respective Shinohara's algorithm are extended to a query class with applications in complex event recognition -- a modern topic from databases.
