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Intelligent recommendation & decision technologies for community-driven requirements engineering
dc.contributor.author | Samer, Ralph |
dc.contributor.author | Stettinger, Martin |
dc.contributor.author | Felfernig, Alexander |
dc.contributor.author | Franch Gutiérrez, Javier |
dc.contributor.author | Falkner, Andreas |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria de Serveis i Sistemes d'Informació |
dc.date.accessioned | 2021-02-03T10:24:21Z |
dc.date.available | 2021-02-03T10:24:21Z |
dc.date.issued | 2020 |
dc.identifier.citation | Samer, 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.isbn | 978-1-64368-101-6 |
dc.identifier.uri | http://hdl.handle.net/2117/336789 |
dc.description.abstract | Requirements 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.sponsorship | The work presented in this paper has been conducted within the scope of the Horizon 2020 project OPENREQ (732463). |
dc.format.extent | 9 p. |
dc.language.iso | eng |
dc.publisher | Ios Press |
dc.rights | Attribution-NonCommercial 4.0 International |
dc.rights.uri | https://creativecommons.org/licenses/by-nc/4.0/ |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Enginyeria del software |
dc.subject.lcsh | Decision-making |
dc.subject.lcsh | Requirements engineering |
dc.title | Intelligent recommendation & decision technologies for community-driven requirements engineering |
dc.type | Conference report |
dc.subject.lemac | Decisió, Presa de |
dc.subject.lemac | Enginyeria de requisits |
dc.contributor.group | Universitat Politècnica de Catalunya. inSSIDE - integrated Software, Service, Information and Data Engineering |
dc.identifier.doi | 10.3233/FAIA200477 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | http://ebooks.iospress.nl/volumearticle/55272 |
dc.rights.access | Open Access |
local.identifier.drac | 30144969 |
dc.description.version | Postprint (published version) |
dc.relation.projectid | info:eu-repo/grantAgreement/EC/H2020/732463/EU/Intelligent Recommendation Decision Technologies for Community-Driven Requirements Engineering/OPENREQ |
local.citation.author | Samer, R.; Stettinger, M.; Felfernig, A.; Franch, X.; Falkner, A. |
local.citation.contributor | European Conference on Artificial Intelligence |
local.citation.pubplace | Amsterdam |
local.citation.publicationName | 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 |
local.citation.startingPage | 3017 |
local.citation.endingPage | 3025 |