Knowledge Extraction from Natural Language Requirements into a Semantic Relation Graph

Schlutter, Aaron; Vogelsang, Andreas

Knowledge Extraction from Natural Language Requirements into a Semantic Relation Graph

dc.contributor.author	Schlutter, Aaron
dc.contributor.author	Vogelsang, Andreas
dc.date.accessioned	2020-04-08T10:17:49Z
dc.date.available	2020-04-08T10:17:49Z
dc.date.issued	2020-05
dc.description.abstract	Knowledge extraction and representation aims to identify information and to transform it into a machine-readable format. Knowledge representations support Information Retrieval tasks such as searching for single statements, documents, or metadata. Requirements specifications of complex systems such as automotive software systems are usually divided into different subsystem specifications. Nevertheless, there are semantic relations between individual documents of the separated subsystems, which have to be considered in further processes (e.g. dependencies). If requirements engineers or other developers are not aware of these relations, this can lead to inconsistencies or malfunctions of the overall system. Therefore, there is a strong need for tool support in order to detects semantic relations in a set of large natural language requirements specifications. In this work we present a knowledge extraction approach based on an explicit knowledge representation of the content of natural language requirements as a semantic relation graph. Our approach is fully automated and includes an NLP pipeline to transform unrestricted natural language requirements into a graph. We split the natural language into different parts and relate them to each other based on their semantic relation. In addition to semantic relations, other relationships can also be included in the graph. We envision to use a semantic search algorithm like spreading activation to allow users to search different semantic relations in the graph.	en
dc.identifier.uri	https://depositonce.tu-berlin.de/handle/11303/10876.2
dc.identifier.uri	http://dx.doi.org/10.14279/depositonce-9772.2
dc.language.iso	en	en
dc.rights.uri	http://rightsstatements.org/vocab/InC/1.0/	en
dc.subject.ddc	004 Datenverarbeitung; Informatik	en
dc.subject.other	knowledge extraction	en
dc.subject.other	requirement engineering	en
dc.subject.other	natural language processing	en
dc.subject.other	semantic relation graph	en
dc.subject.other	spreading activation	en
dc.title	Knowledge Extraction from Natural Language Requirements into a Semantic Relation Graph	en
dc.type	Conference Object	en
dc.type.version	acceptedVersion	en
dcterms.bibliographicCitation.doi	10.1145/3387940.3392162	en
dcterms.bibliographicCitation.originalpublishername	Association for Computing Machinery (ACM)	en
dcterms.bibliographicCitation.originalpublisherplace	New York, NY	en
dcterms.bibliographicCitation.proceedingstitle	IEEE/ACM 42nd International Conference on Software Engineering Workshops (ICSEW’20)	en
tub.accessrights.dnb	free	en
tub.affiliation	Fak. 4 Elektrotechnik und Informatik::Inst. Telekommunikationssysteme::FG IT-basierte Fahrzeuginnovationen	de
tub.affiliation.faculty	Fak. 4 Elektrotechnik und Informatik	de
tub.affiliation.group	FG IT-basierte Fahrzeuginnovationen	de
tub.affiliation.institute	Inst. Telekommunikationssysteme	de
tub.publisher.universityorinstitution	Technische Universität Berlin	en