Paper Info
Title
Process ontology development using natural language processing: a multiple case study.
Abstract
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.
Year
DOI
Venue
2019
10.1108/BPMJ-05-2018-0144
BUSINESS PROCESS MANAGEMENT JOURNAL
Keywords
DocType
Volume
Process ontology,Ontology development,Business process modelling,Natural language processing
Journal
25.0
Issue
ISSN
Citations 
6.0
1463-7154
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Özge Gürbüz100.34
Fethi Rabhi242750.68
Onur Demirörs334656.17