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dc.contributor.authorSamer, Ralph
dc.contributor.authorStettinger, Martin
dc.contributor.authorFelfernig, Alexander
dc.contributor.authorFranch Gutiérrez, Javier
dc.contributor.authorFalkner, Andreas
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Serveis i Sistemes d'Informació
dc.date.accessioned2021-02-03T10:24:21Z
dc.date.available2021-02-03T10:24:21Z
dc.date.issued2020
dc.identifier.citationSamer, R. [et al.]. Intelligent recommendation & decision technologies for community-driven requirements engineering. A: European Conference on Artificial Intelligence. "ECAI 2020, 24th European Conference on Artificial Intelligence: 29 August–8 September 2020, Santiago de Compostela, Spain: including 10th Conference on Prestigious Applications of Artificial Intelligence (PAIS 2020): proceedings". Amsterdam: Ios Press, 2020, p. 3017-3025. ISBN 978-1-64368-101-6. DOI 10.3233/FAIA200477.
dc.identifier.isbn978-1-64368-101-6
dc.identifier.urihttp://hdl.handle.net/2117/336789
dc.description.abstractRequirements Engineering (RE) represents a critical phase in the management and planning of software projects. One of the main reasons for project failure is missing or incomplete RE. In order to reduce the risk of project failure, there exists a high and urgent demand for applying intelligent technologies in RE. Since the RE process is mainly decision- and community-driven, Recommender Systems are supposed to be applied in this particular context to support stakeholders in decision-making and, hence, to increase the quality of the decisions taken by the stakeholders. This paper introduces a variety of innovative recommendation tools developed within the scope of the European Horizon 2020 research project OPENREQ. Moreover, we give an overview of user studies conducted to evaluate our approaches and present final results of selected studies. The study results indicate that the developed concepts have the potential to significantly improve the quality of requirements definition and requirements prioritization.
dc.description.sponsorshipThe work presented in this paper has been conducted within the scope of the Horizon 2020 project OPENREQ (732463).
dc.format.extent9 p.
dc.language.isoeng
dc.publisherIos Press
dc.rightsAttribution-NonCommercial 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.subjectÀrees temàtiques de la UPC::Informàtica::Enginyeria del software
dc.subject.lcshDecision-making
dc.subject.lcshRequirements engineering
dc.titleIntelligent recommendation & decision technologies for community-driven requirements engineering
dc.typeConference report
dc.subject.lemacDecisió, Presa de
dc.subject.lemacEnginyeria de requisits
dc.contributor.groupUniversitat Politècnica de Catalunya. inSSIDE - integrated Software, Service, Information and Data Engineering
dc.identifier.doi10.3233/FAIA200477
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://ebooks.iospress.nl/volumearticle/55272
dc.rights.accessOpen Access
local.identifier.drac30144969
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/732463/EU/Intelligent Recommendation Decision Technologies for Community-Driven Requirements Engineering/OPENREQ
local.citation.authorSamer, R.; Stettinger, M.; Felfernig, A.; Franch, X.; Falkner, A.
local.citation.contributorEuropean Conference on Artificial Intelligence
local.citation.pubplaceAmsterdam
local.citation.publicationNameECAI 2020, 24th European Conference on Artificial Intelligence: 29 August–8 September 2020, Santiago de Compostela, Spain: including 10th Conference on Prestigious Applications of Artificial Intelligence (PAIS 2020): proceedings
local.citation.startingPage3017
local.citation.endingPage3025


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