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An Automatic Approach for Extracting Process Knowledge from the Web

机译:从Web提取过程知识的自动方法

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Process knowledge, such as tasks involved in a process and the control flow and data flow among tasks, is critical for designing business processes. Such process knowledge enables service composition which integrates different services to implement business processes. In the current state of practice, business processes are primarily designed by experienced business analysts who have extensive process knowledge. It is challenging for novice business analysts and non-professional end-users to identify a complete set of services to orchestrate a well-defined business process due to the lack of process knowledge. In this paper, we propose an approach to extract process knowledge from existing commercial applications on the Web. Our approach uses a Web search engine to find websites containing process knowledge on the Internet. By analyzing the content and the structure of relevant websites, we extract the process knowledge from various websites and merge the process knowledge to generate an integrated ontology with rich process knowledge. We conduct a case study to compare our approach with a tool that extracts ontologies from textual sources. The result of the case study shows that our approach can extract process knowledge from online applications with higher precision and recall comparing to the ontology learning tool.
机译:流程知识(例如流程中涉及的任务以及任务之间的控制流和数据流)对于设计业务流程至关重要。这种流程知识使服务组合能够集成不同的服务以实现业务流程。在当前的实践状态中,业务流程主要是由经验丰富的业务分析师设计的,他们具有丰富的流程知识。对于新手业务分析师和非专业最终用户而言,由于缺乏流程知识,他们难以确定一套完整的服务来协调定义良好的业务流程,这是一项挑战。在本文中,我们提出了一种从Web上现有的商业应用程序中提取过程知识的方法。我们的方法使用Web搜索引擎在Internet上查找包含过程知识的网站。通过分析相关网站的内容和结构,我们从各个网站中提取过程知识,并将过程知识进行合并,以生成具有丰富过程知识的集成本体。我们进行了一个案例研究,以将我们的方法与从文本来源中提取本体的工具进行比较。案例研究的结果表明,与本体学习工具相比,我们的方法可以从在线应用程序中更准确地提取过程知识,并具有良好的回忆性。

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