Purpose Integrating ontologies with process modeling has gained increasing attention in recent years since it enhances data representations and makes it easier to query, store and reuse knowledge at the semantic level. The authors focused on a process and ontology integration approach by extracting the activities, roles and other concepts related to the process models from organizational sources using natural language processing techniques. As part of this study, a process ontology population (PrOnPo) methodology and tool is developed, which uses natural language parsers for extracting and interpreting the sentences and populating an event-driven process chain ontology in a fully automated or semi-automated (user assisted) manner. The purpose of this paper is to present applications of PrOnPo tool in different domains. Design/methodology/approach A multiple case study is conducted by selecting five different domains with different types of guidelines. Process ontologies are developed using the PrOnPo tool in a semi-automated and fully automated fashion and manually. The resulting ontologies are compared and evaluated in terms of time-effort and recall-precision metrics. Findings From five different domains, the results give an average of 70 percent recall and 80 percent precision for fully automated usage of the PrOnPo tool, showing that it is applicable and generalizable. In terms of efficiency, the effort spent for process ontology development is decreased from 250 person-minutes to 57 person-minutes (semi-automated). Originality/value The PrOnPo tool is the first one to automatically generate integrated process ontologies and process models from guidelines written in natural language.

中文翻译：

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使用自然语言处理的过程本体开发：多案例研究

目的近年来，将本体与过程建模集成在一起已经引起了越来越多的关注，因为它增强了数据表示，并使得更易于在语义级别上查询，存储和重用知识。作者通过使用自然语言处理技术从组织来源中提取与流程模型相关的活动，角色和其他概念，从而专注于流程和本体集成方法。作为这项研究的一部分，开发了一种过程本体填充（PrOnPo）方法和工具，该方法和工具使用自然语言解析器提取和解释句子，并在全自动或半自动化（用户协助下）填充事件驱动的过程链本体。 ）方式。本文的目的是介绍PrOnPo工具在不同领域中的应用。设计/方法/方法通过选择具有不同类型指南的五个不同领域来进行多案例研究。使用PrOnPo工具以半自动化和全自动方式并手动开发过程本体。根据时间量和召回精度指标对生成的本体进行比较和评估。从五个不同的领域得出的结果对于完全自动化地使用PrOnPo工具，结果给出了70％的召回率和80％的精度，表明该工具适用且可推广。在效率方面，用于过程本体开发的精力从250人/分钟减少到57人/分钟（半自动化）。