Intelligent Recommendation & Decision Technologies for Community-Driven Requirements Engineering

Ralph Samer, Martin Stettinger, Alexander Felfernig, Xavier Franch, Andreas Falkner

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Requirements Engineering (RE) represents a criticalphase in the management and planning of software projects. One ofthe main reasons for project failure is missing or incomplete RE. Inorder to reduce the risk of project failure, there exists a high andurgent demand for applying intelligent technologies in RE. Sincethe RE process is mainly decision- and community-driven,Recom-mender Systemsare supposed to be applied in this particular con-text to support stakeholders in decision-making and, hence, to in-crease the quality of the decisions taken by the stakeholders. Thispaper introduces a variety of innovative recommendation tools devel-oped within the scope of the European Horizon 2020 research projectOPENREQ. Moreover, we give an overview of user studies conductedto evaluate our approaches and present final results of selected stud-ies. The study results indicate that the developed concepts have thepotential to significantly improve the quality of requirements defini-tion and requirements prioritization.
Original languageEnglish
Title of host publication24th European Conference on Artificial Intelligence (ECAI '20)
Number of pages9
Publication statusSubmitted - 2020
EventECAI 2020 - 24th European Conference on Artificial Intelligence - Virtuell
Duration: 8 Jun 202012 Jun 2020
Conference number: 24
http://ecai2020.eu/

Conference

ConferenceECAI 2020 - 24th European Conference on Artificial Intelligence
Abbreviated titleECAI 2020
CityVirtuell
Period8/06/2012/06/20
Internet address

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  • Cite this

    Samer, R., Stettinger, M., Felfernig, A., Franch, X., & Falkner, A. (2020). Intelligent Recommendation & Decision Technologies for Community-Driven Requirements Engineering. Manuscript submitted for publication. In 24th European Conference on Artificial Intelligence (ECAI '20)