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2012 20th IEEE International Requirements Engineering Conference (RE)
Using collective intelligence to detect pragmatic ambiguities
Chicago, IL, USA USA
September 24-September 28
ISBN: 978-1-4673-2783-1
| ASCII Text | x | ||
| Alessio Ferrari, Stefania Gnesi, "Using collective intelligence to detect pragmatic ambiguities," 2012 20th IEEE International Requirements Engineering Conference (RE), pp. 191-200, 2012 20th IEEE International Requirements Engineering Conference (RE), 2012. | |||
| BibTex | x | ||
| @article{ 10.1109/RE.2012.6345803, author = {Alessio Ferrari and Stefania Gnesi}, title = {Using collective intelligence to detect pragmatic ambiguities}, journal ={2012 20th IEEE International Requirements Engineering Conference (RE)}, volume = {0}, year = {2012}, issn = {1090-750X}, pages = {191-200}, doi = {http://doi.ieeecomputersociety.org/10.1109/RE.2012.6345803}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - 2012 20th IEEE International Requirements Engineering Conference (RE) TI - Using collective intelligence to detect pragmatic ambiguities SN - 1090-750X SP191 EP200 A1 - Alessio Ferrari, A1 - Stefania Gnesi, PY - 2012 KW - pragmatic ambiguity KW - requirements/specifications analysis KW - natural language KW - ambiguity detection VL - 0 JA - 2012 20th IEEE International Requirements Engineering Conference (RE) ER - | |||
This paper presents a novel approach for pragmatic ambiguity detection in natural language (NL) requirements specifications defined for a specific application domain. Starting from a requirements specification, we use a Web-search engine to retrieve a set of documents focused on the same domain of the specification. From these domain-related documents, we extract different knowledge graphs, which are employed to analyse each requirement sentence looking for potential ambiguities. To this end, an algorithm has been developed that takes the concepts expressed in the sentence and searches for corresponding “concept paths” within each graph. The paths resulting from the traversal of each graph are compared and, if their overall similarity score is lower than a given threshold, the requirements specification sentence is considered ambiguous from the pragmatic point of view. A proof of concept is given throughout the paper to illustrate the soundness of the proposed strategy.
Index Terms:
pragmatic ambiguity,requirements/specifications analysis,natural language,ambiguity detection
Citation:
Alessio Ferrari, Stefania Gnesi, "Using collective intelligence to detect pragmatic ambiguities," re, pp.191-200, 2012 20th IEEE International Requirements Engineering Conference (RE), 2012
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