IRDec 24, 2021

Automatic extraction of requirements expressed in industrial standards : a way towards machine readable standards ?

arXiv:2112.13091v12 citations
Originality Synthesis-oriented
AI Analysis

This work addresses the challenge of making industrial standards machine-readable for domain-specific applications, but it appears incremental as it builds on existing NLP and semantic annotation techniques.

The project tackled the problem of automatically extracting requirements from industrial standards for electrical appliances by developing a semantic analysis approach, resulting in the creation of an ontology and a system for indexing and storing requirements for query processing.

The project, under industrial funding, presented in this publication aims at the semantic analysis of a normative document describing requirements applicable to electrical appliances. The objective of the project is to build a semantic approach to extract and automatically process information related to the requirements contained in the standard. To this end, the project has been divided into three parts, covering the analysis of the requirements document, the extraction of relevant information and creation of the ontology and the comparison with other approaches. The first part of our work deals with the analysis of the requirements document under study. The study focuses on the specificity of the sentence structure, the use of particular words and vocabulary related to the representation of the requirements. The aim is to propose a representation facilitating the extraction of information, used in the second part of the study. In the second part, the extraction of relevant information is conducted in two ways: manual (the ontology being built by hand), semi-automatic (using semantic annotation software and natural language processing techniques). Whatever the method used, the aim of this extraction is to create the concept dictionary, then the ontology, enriched as the document is scanned and understood by the system. Once the relevant terms have been identified, the work focuses on identifying and representing the requirements, separating the textual writing from the information given in the tables. The automatic processing of requirements involves the extraction of sentences containing terms identified as relevant to a requirement. The identified requirement is then indexed and stored in a representation that can be used for query processing.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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