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A Machine-Based Personality Oriented Team Recommender for Software Development Organizations

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dc.contributor.author Yılmaz, Murat
dc.contributor.author Al-Taei, Ali
dc.contributor.author O'Connor, Rory V.
dc.date.accessioned 2020-04-29T20:49:41Z
dc.date.available 2020-04-29T20:49:41Z
dc.date.issued 2015
dc.identifier.citation Yılmaz, Murat; Al-Taei, A.; O’Connor, R.V., "A Machine-Based Personality Oriented Team Recommender for Software Development Organizations", Communications In Computer and Information Science, Vol. 543, pp. 75-86, (2015). tr_TR
dc.identifier.isbn 978-331924646-8
dc.identifier.issn 18650929
dc.identifier.uri http://hdl.handle.net/20.500.12416/3505
dc.description.abstract Hiring the right person for the right job is always a challenging task in software development landscapes. To bridge this gap, software firms start using psychometric instruments for investigating the personality types of software practitioners. In our previous research, we have developed an MBTI-like instrument to reveal the personality types of software practitioners. This study aims to develop a personality-based team recommender mechanism to improve the effectiveness of software teams. The mechanism is based on predicting the possible patterns of teams using a machine-based classifier. The classifier is trained with empirical data (e.g. personality types, job roles), which was collected from 52 software practitioners working on five different software teams. 12 software practitioners were selected for the testing process who were recommended by the classifier to work for these teams. The preliminary results suggest that a personality-based team recommender system may provide an effective approach as compared with ad-hoc methods of team formation in software development organizations. Ultimately, the overall performance of the proposed classifier was 83.3%. These findings seem acceptable especially for tasks of suggestion where individuals might be able to fit in more than one team. tr_TR
dc.language.iso eng tr_TR
dc.publisher Springer Verlag tr_TR
dc.relation.isversionof 10.1007/978-3-319-24647-5_7 tr_TR
dc.rights info:eu-repo/semantics/closedAccess tr_TR
dc.subject MBTI tr_TR
dc.subject Multilayer Perceptron tr_TR
dc.subject Neural Networks tr_TR
dc.subject Organizational Improvement tr_TR
dc.subject Personality Profiling tr_TR
dc.subject Personnel Recommendation System tr_TR
dc.title A Machine-Based Personality Oriented Team Recommender for Software Development Organizations tr_TR
dc.type bookPart tr_TR
dc.relation.journal Communications In Computer and Information Science tr_TR
dc.identifier.volume 543 tr_TR
dc.identifier.startpage 75 tr_TR
dc.identifier.endpage 86 tr_TR
dc.contributor.department Çankaya Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü tr_TR


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