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Identification of Cross-Domain Ambiguity with Language Models

Contributo in Atti di convegno
Data di Pubblicazione:
2018
Abstract:
During requirements elicitation, different stakeholders with diverse backgrounds and skills need to effectively communicate to reach a shared understanding of the problem at hand. Linguistic ambiguity due to terminological discrepancies may occur between stakeholders that belong to different technical domains. If not properly addressed, ambiguity can create frustration and distrust during requirements elicitation meetings, and lead to problems at later stages of development. This paper presents a natural language processing approach to identify ambiguous terms between different domains. The approach is based on building domain-specific language models, one for each stakeholders' domain. Word embeddings from each language model are compared in order to measure the differences of use of a word, thus estimating its potential ambiguity across the domains of interest. The proposed strategy can be useful to prepare lists of dangerous terms to take into account during requirements elicitation meetings, such as workshops, or focus groups, when these involve stakeholders from distant domains.
Tipologia CRIS:
04.01 Contributo in Atti di convegno
Keywords:
Requirement Engineering
Elenco autori:
Gnesi, Stefania; Esuli, Andrea; Ferrari, Alessio
Autori di Ateneo:
ESULI ANDREA
FERRARI ALESSIO
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/359363
Link al Full Text:
https://iris.cnr.it//retrieve/handle/20.500.14243/359363/20784/prod_401324-doc_160412.pdf
Titolo del libro:
2018 5th International Workshop on Artificial Intelligence for Requirements Engineering (AIRE)
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URL

https://ieeexplore.ieee.org/document/8501308
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