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Methods and techniques for discovering taxonomies of behavioral process models

机译:发现行为过程模型分类法的方法和技术

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摘要

Modeling behavioral aspects of business processes is a hard and costly task, which usually requires heavy intervention of business experts. This explains the increasing attention given to process mining techniques, which automatically extract behavioral process models from log data. In the case of complex processes, however, the models identified by classical process mining techniques are hardly useful to analyze business operations at a suitable abstraction level. In fact, the need of process abstraction emerged in several application scenarios, and abstraction methods are already supported in some business-management platforms, which allow users to manually define abstract views for the process at hand. Therefore, it comes with no surprise that process mining research recently considered the issue of mining processes at different abstraction levels, mainly in the form of a taxonomy of process models, as to overcome the drawbacks of traditional approaches. This paper presents a general framework for the discovery of such a taxonomy, and offers a survey of different kinds of basic techniques that can be exploited to this purpose: (1) workflow modeling and discovery techniques, (2) clustering techniques enabling the discovery of different behavioral process classes, and (3) activity abstraction techniques for associating a generalized process model with each higher level taxonomy node. (c) 2013 Wiley Periodicals, Inc.
机译:对业务流程的行为方面进行建模是一项艰巨而昂贵的任务,通常需要业务专家的大力干预。这解释了对过程挖掘技术的日益关注,该技术从日志数据中自动提取行为过程模型。但是,在复杂流程的情况下,经典流程挖掘技术所识别的模型对于在适当的抽象级别上分析业务操作几乎没有用。实际上,在一些应用程序场景中出现了对流程抽象的需求,并且某些业务管理平台已经支持了抽象方法,这些平台允许用户手动定义手头流程的抽象视图。因此,不足为奇的是,过程挖掘研究最近考虑了不同抽象级别的挖掘过程问题,主要以过程模型的分类法形式,以克服传统方法的弊端。本文为发现这种分类法提供了一个通用框架,并概述了可用于此目的的各种基本技术:(1)工作流建模和发现技术,(2)支持发现分类的聚类技术不同的行为过程类,以及(3)用于将广义过程模型与每个更高级别的分类法节点相关联的活动抽象技术。 (c)2013 Wiley期刊公司

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