Ontologiebasierte Entwicklung von Anforderungsspezifikationen im Automotive- Umfeld

Schraps, Mathias; Allmann, Christian

doi:10.1007/bf03323509

Cited by 2 publications

(1 citation statement)

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“…A well-defined taxonomy can support the formulation of requirements by providing a common system understanding and ensuring consistent term usage. Furthermore, it is possible to add relations and manage these dependencies between concepts in the taxonomy and their corresponding usage in requirement statements in order to build up a requirements ontology to support RE tasks in early phases of automotive software development [1]. Once this knowledge is specified, it can be used to accompany the whole RE process of a project and possibly also serve as basis for future projects.…”

Section: Introductionmentioning

confidence: 99%

Taxonomy Extraction from Automotive Natural Language Requirements Using Unsupervised Learning

Ringsquandl¹,

Schraps²

2014

IJNLC

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In this paper we present a novel approach to semi-automatically learn concept hierarchies from natural language requirements of the automotive industry. The approach is based on the distributional hypothesis and the special characteristics of domain-specific German compounds. We extract taxonomies by using clustering techniques in combination with general thesauri. Such a taxonomy can be used to support requirements engineering in early stages by providing a common system understanding and an agreedupon terminology. This work is part of an ontology-driven requirements engineering process, which builds on top of the taxonomy. Evaluation shows that this taxonomy extraction approach outperforms common hierarchical clustering techniques.

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Section: Introductionmentioning

confidence: 99%