2016
Conference article  Open Access

Ensuring action: identifying unclear actor specifications in textual business process descriptions

Sanne U., Witschel H. F., Ferrari A., Gnesi S.

D.2 SOFTWARE ENGINEERING  Document quality  Natural language processing  Business process management  Quality assessment  Ambiguity  D.2.1 SOFTWARE ENGINEERING. Requirements/Specifications 

In many organisations, business process (BP) descriptions are available in the form of written procedures, or operational manuals. These documents are expressed in informal natural language, which is inherently open to different interpretations. Hence, the content of these documents might be incorrectly interpreted by those who have to put the process into practice. It is therefore important to identify language defects in written BP descriptions, to ensure that BPs are properly carried out. Among the potential defects, one of the most relevant for BPs is the absence of clear actors in action-related sentences. Indeed, an unclear actor might lead to a missing responsibility, and, in turn, to activities that are never performed. This paper aims at identifying unclear actors in BP descriptions expressed in natural language. To this end, we define an algorithm named ABIDE, which leverages rule-based natural language processing (NLP) techniques. We evaluate the algorithm on a manually annotated data-set of 20 real-world BP descriptions (1,029 sentences). ABIDE achieves a recall of 87%, and a precision of 56%. We consider these results promising. Improvements of the algorithm are also discussed in the paper.

Source: International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, pp. 140–147, Porto, Portugal, 9-11 November 2016


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BibTeX entry
@inproceedings{oai:it.cnr:prodotti:362680,
	title = {Ensuring action: identifying unclear actor specifications in textual business process descriptions},
	author = {Sanne U. and Witschel H.  F. and Ferrari A. and Gnesi S.},
	doi = {10.5220/0006040301400147},
	booktitle = {International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, pp. 140–147, Porto, Portugal, 9-11 November 2016},
	year = {2016}
}

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