ReSySTER: A hybrid recommender system for Scrum team roles based on fuzzy and rough sets
Ricardo Colomo-Palacios ; Israel González-Carrasco ; José Luis López-Cuadrado ; Ángel García-Crespo
International Journal of Applied Mathematics and Computer Science, Tome 22 (2012), p. 801-816 / Harvested from The Polish Digital Mathematics Library

Agile development is a crucial issue within software engineering because one of the goals of any project leader is to increase the speed and flexibility in the development of new commercial products. In this sense, project managers must find the best resource configuration for each of the work packages necessary for the management of software development processes in order to keep the team motivated and committed to the project and to improve productivity and quality. This paper presents ReSySTER, a hybrid recommender system based on fuzzy logic, rough set theory and semantic technologies, aimed at helping project leaders to manage software development projects. The proposed system provides a powerful tool for project managers supporting the development process in Scrum environments and helping to form the most suitable team for different work packages. The system has been evaluated in a real scenario of development with the Scrum framework obtaining promising results.

Publié le : 2012-01-01
EUDML-ID : urn:eudml:doc:244504
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     author = {Ricardo Colomo-Palacios and Israel Gonz\'alez-Carrasco and Jos\'e Luis L\'opez-Cuadrado and \'Angel Garc\'\i a-Crespo},
     title = {ReSySTER: A hybrid recommender system for Scrum team roles based on fuzzy and rough sets},
     journal = {International Journal of Applied Mathematics and Computer Science},
     volume = {22},
     year = {2012},
     pages = {801-816},
     zbl = {1292.90003},
     language = {en},
     url = {http://dml.mathdoc.fr/item/bwmeta1.element.bwnjournal-article-amcv22z4p801bwm}
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Ricardo Colomo-Palacios; Israel González-Carrasco; José Luis López-Cuadrado; Ángel García-Crespo. ReSySTER: A hybrid recommender system for Scrum team roles based on fuzzy and rough sets. International Journal of Applied Mathematics and Computer Science, Tome 22 (2012) pp. 801-816. http://gdmltest.u-ga.fr/item/bwmeta1.element.bwnjournal-article-amcv22z4p801bwm/

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