On the Expressiveness of Languages for Complex Event Recognition

Alejandro Grez, Cristian Riveros, M. Ugarte, Stijn Vansummeren
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引用次数: 12

Abstract

Complex Event Recognition (CER for short) has recently gained attention as a mechanism for detecting patterns in streams of continuously arriving event data. Numerous CER systems and languages have been proposed in the literature, commonly based on combining operations from regular expressions (sequencing, iteration, and disjunction) and relational algebra (e.g., joins and filters). While these languages are naturally first-order, meaning that variables can only bind single elements, they also provide capabilities for filtering sets of events that occur inside iterative patterns; for example requiring sequences of numbers to be increasing. Unfortunately, these type of filters usually present ad-hoc syntax and under-defined semantics, precisely because variables cannot bind sets of events. As a result, CER languages that provide filtering of sequences commonly lack rigorous semantics and their expressive power is not understood. In this paper we embark on two tasks: First, to define a denotational semantics for CER that naturally allows to bind and filter sets of events; and second, to compare the expressive power of this semantics with that of CER languages that only allow for binding single events. Concretely, we introduce Set-Oriented Complex Event Logic (SO-CEL for short), a variation of the CER language introduced in [17] in which all variables bind to sets of matched events. We then compare SO-CEL with CEL, the CER language of [17] where variables bind single events. We show that they are equivalent in expressive power when restricted to unary predicates but, surprisingly, incomparable in general. Nevertheless, we show that if we restrict to sets of binary predicates, then SO-CEL is strictly more expressive than CEL. To get a better understanding of the expressive power, computational capabilities, and limitations of SO-CEL, we also investigate the relationship between SO-CEL and Complex Event Automata (CEA), a natural computational model for CER languages. We define a property on CEA called the *-property and show that, under unary predicates, SO-CEL captures precisely the subclass of CEA that satisfy this property. Finally, we identify the operations that SO-CEL is lacking to characterize CEA and introduce a natural extension of the language that captures the complete class of CEA under unary predicates. 2012 ACM Subject Classification Information systems → Data streams; Information systems → Query operators; Theory of computation → Formal languages and automata theory
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复杂事件识别中语言的表达性研究
复杂事件识别(Complex Event Recognition,简称CER)作为一种在连续到达的事件数据流中检测模式的机制,最近受到了人们的关注。文献中已经提出了许多CER系统和语言,通常基于正则表达式(排序、迭代和析取)和关系代数(例如连接和过滤器)的组合操作。虽然这些语言自然是一阶的,这意味着变量只能绑定单个元素,但它们也提供了过滤迭代模式中发生的事件集的功能;例如要求数字序列是递增的。不幸的是,这些类型的过滤器通常呈现特别的语法和未定义的语义,这正是因为变量不能绑定事件集。因此,提供序列过滤的CER语言通常缺乏严格的语义,并且无法理解它们的表达能力。在本文中,我们着手两项任务:首先,为CER定义一个指称语义,自然地允许绑定和过滤事件集;第二,将此语义的表达能力与仅允许绑定单个事件的CER语言的表达能力进行比较。具体来说,我们引入了面向集合的复杂事件逻辑(Set-Oriented Complex Event Logic,简称SO-CEL),这是[17]中引入的CER语言的一种变体,其中所有变量绑定到匹配的事件集。然后,我们将SO-CEL与[17]的CER语言CEL进行比较,其中变量绑定单个事件。我们表明,当限制到一元谓词时,它们在表达能力上是相等的,但令人惊讶的是,在一般情况下是不可比较的。然而,我们证明,如果我们将其限制为二进制谓词集,那么SO-CEL严格地比CEL更具表现力。为了更好地理解SO-CEL的表达能力、计算能力和局限性,我们还研究了SO-CEL与复杂事件自动机(CEA)之间的关系,CEA是CER语言的一种自然计算模型。我们在CEA上定义了一个称为*-属性的属性,并表明,在一元谓词下,SO-CEL精确地捕获满足该属性的CEA的子类。最后,我们确定了SO-CEL缺乏表征CEA的操作,并引入了语言的自然扩展,该语言在一元谓词下捕获了完整的CEA类。2012 ACM学科分类信息系统→数据流;信息系统→查询操作员;计算理论→形式语言和自动机理论
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