Extending Shinohara's Algorithm for Computing Descriptive (Angluin-Style) Patterns to Subsequence Patterns
Abstract
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-Mei{\ss}ner 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.
Cite
@article{arxiv.2206.13918,
title = {Extending Shinohara's Algorithm for Computing Descriptive (Angluin-Style) Patterns to Subsequence Patterns},
author = {Markus L. Schmid},
journal= {arXiv preprint arXiv:2206.13918},
year = {2022}
}