Conference proceeding
Optimizing Named Entity Recognition for Improving Logical Formulae Abstraction from Technical Requirements Documents
International Conference on Dependable Systems and Their Applications (Online), pp 211-222
10 Aug 2023
Abstract
Requirements engineering involves obtaining a complete and consistent set of requirements for a particular system. Requirement engineers often formulate requirements in a textual form where automated proving consistency and completeness is impossible. Converting textual requirements into logical formulae would enable analysis and reasoning tasks. In this work, we contribute to converting textual requirements into logical sentences. In particular, we focus on the named entity recognition task on industrial requirements documents to improve semantic abstraction using logical formalisms. We found that using general-purpose models for named entity recognition is not working well for specialized domains. Hence, we focused on retraining such models and investigated the ratio of domain-specific versus general-purpose data for retraining. Our results demonstrate significant improvements in F1-Scores compared to the respective pre-trained baseline models when performing domain-specific tasks.
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Details
- Title
- Optimizing Named Entity Recognition for Improving Logical Formulae Abstraction from Technical Requirements Documents
- Creators
- Alexander Perko - Graz University of TechnologyHaoran Zhao - Drexel UniversityFranz Wotawa - Graz University of Technology
- Publication Details
- International Conference on Dependable Systems and Their Applications (Online), pp 211-222
- Publisher
- IEEE
- Number of pages
- 12
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Scopus ID
- 2-s2.0-85179522850
- Other Identifier
- 991022207163404721