Authors:
Ulf Sanne
1
;
Hans Friedrich Witschel
1
;
Alessio Ferrari
2
and
Stefania Gnesi
2
Affiliations:
1
Fachhochschule Nordwestschweiz, Switzerland
;
2
CNR, Italy
Keyword(s):
Business Process Management, Quality Assessment, Natural Language Processing.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Business Process Management
;
Communication, Collaboration and Information Sharing
;
e-Business
;
Enterprise Engineering
;
Enterprise Information Systems
;
Knowledge Management and Information Sharing
;
Knowledge-Based Systems
;
Symbolic Systems
;
Tools and Technology for Knowledge Management
Abstract:
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 an
notated 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.
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