Document - QuOD: An NLP Tool to Improve the Quality of Business Process Descriptions

2019

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QuOD: An NLP Tool to Improve the Quality of Business Process Descriptions

Ferrari A., Spagnolo G. O., Fiscella A., Parente G.

Business process NLP Requirements engineering

In real-world organisations, business processes (BPs) are often described by means of natural language (NL) documents. Indeed, although semi-formal graphical notations exist to model BPs, most of the legacy process knowledge--when not tacit--is still conveyed through textual procedures or operational manuals, in which the BPs are specified. This is particularly true for public administrations (PAs), in which a large variety of BPs exist (e.g., definition of tenders, front-desk support) that have to be understood and put into practice by civil servants. [Question/problem] Incorrect understanding of the BP descriptions in PAs may cause delays in the delivery of services to citizens, or, in some cases, incorrect execution of the BPs. [Principal idea/results] In this paper, we present the development of an NLP-based tool named QuOD (Quality Analyser for Official Documents), oriented to detect linguistic defects in BP descriptions and to provide recommendations for improvements. [Contribution] QuOD is the first tool that addresses the problem of identifying NL defects in BP descriptions of PAs. The tool is available online at http://narwhal.it/quod/index.html.

Source: From Software Engineering to Formal Methods and Tools, and Back Essays Dedicated to Stefania Gnesi on the Occasion of Her 65th Birthday, edited by ter Beek M.H.; Fantechi A.; Semini L., pp. 267–281, 2019

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@inbook{oai:it.cnr:prodotti:415915,
	title = {QuOD: An NLP Tool to Improve the Quality of Business Process Descriptions},
	author = {Ferrari A. and Spagnolo G.  O. and Fiscella A. and Parente G.},
	doi = {10.1007/978-3-030-30985-5_17},
	booktitle = {From Software Engineering to Formal Methods and Tools, and Back Essays Dedicated to Stefania Gnesi on the Occasion of Her 65th Birthday, edited by ter Beek M.H.; Fantechi A.; Semini L., pp. 267–281, 2019},
	year = {2019}
}