Social Validation of Solutions in the Context of Online Communities

Abstract : Online Communities are considered as a new organizational structure that allows individuals and groups of persons to collaborate and share their knowledge and experiences. These members need technological support in order to facilitate their learning activities (e.g. during a problem solving process).We address in this paper the problem of social validation, our aim being to support members of Online Communities of Learners to validate the proposed solutions. Our approach is based on the members’ evaluations: we apply three machine learning techniques, namely a Genetic Algorithm, Artificial Neural Networks and the Naïve Bayes approach. The main objective is to determine a validity rating of a given solution. A preliminary experimentation of our approach within a Community of Learners whose main objective is to collaboratively learn the Java language shows that Neural Networks represent the most suitable approach in this context.
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Lydia Driff, Lamia Berkani, Ahmed Guessoum, Abdellah Bendjahel. Social Validation of Solutions in the Context of Online Communities. 5th International Conference on Computer Science and Its Applications (CIIA), May 2015, Saida, Algeria. pp.93-104, ⟨10.1007/978-3-319-19578-0_8⟩. ⟨hal-01789983⟩

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