Business Process Mining and Rules Detection for Unstructured Information
Business Process Mining and Rules Detection for Unstructured Information
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非结构化信息的业务流程挖掘和规则检测
DOI：
10.1109/micai.2010.22
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发表时间：
2010
期刊：
影响因子：
--
通讯作者：
N. Hernández
中科院分区：
文献类型：
--
作者：
Dafne A. Rosso;Raul A. Trejo;M. González;N. Hernández
在本文中，我们展示了如何通过规则、模式和因果关系检测，在已知业务流程的非结构化报告中找到不完整或不完整的流程的证据。流程活动的先验分类和概率被用作分析和规则检测的输入。在该方法中，我们使用与流程活动相关联的领域特定本体来改进先前的结果，其中，通过SLM来检测文档集中流程的出现
In this article we show how to find evidence of incomplete or fractured processes in non-structured reports of known business processes, by means of rules, patterns and detection of cause-effect relationships. A priori classifications and probabilities of process activities are used as inputs for the analysis and rules detection. In this method we use a domain-specific ontology associated to process activities in order to improve on previous results, where occurrence of a process in a document set was detected by means of SLM