ReSySTER: A hybrid recommender system for Scrum team roles based on fuzzy and rough sets

Abstract

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.

Formalization of Technological Knowledge in the Field of Metallurgy using Document Classification Tools Supported with Semantic Techniques

“…This method of defining a set implies the potential for ambiguity, hence the rough set is composed of the lower and upper approximations. All objects decision table (elements of the set) are determined by a binary Indiscernibility relation (IND), which is key in rough set theory [24]. Its definition is as follows: Let it be a decision table DT = U, C, D,V, f, where C  D = Q and any subset of attributes P  Q. Indiscernibility relation is:…”

Game-theoretic rough sets for recommender systems

“…The rough set theory has recently gained some attention in the recommender systems research [5,8,15,17,24,33]. It has been used with different intends in designing, developing and implementing recommender systems, such as, to obtain rules for determining the competence of players in a game [8], to visualize user preferences in menu selection [17], to reduce attributes for determining useful keywords in web page recommendations [5] and to deal with the problem of missing ratings (also termed as the problem of sparsity) [15].…”

Methods of Computational Intelligence in the Context of Quality Assurance in Foundry Products

“…It is used in advanced devices like cars, washing machines, and smartphones, and also in simple cylinders. Fuzzy models allow reducing the number of rules and a smooth transition in the areas of membership, which allows building models of reasoning similar to the reasoning carried out by man [12]. In the field of metallurgy, fuzzy models are used not only in process control but also in materials science to achieve automation in making multiple decisions.…”