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Social Validation of Solutions in the Context of Online Communities

An Expertise-Based Learning Approach

  • Conference paper

Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT,volume 456)

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.

Keywords

  • Learning Community
  • Social Validation
  • Expertise-Based Learning
  • Machine Learning

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Correspondence to Lydia Nahla Driff .

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© 2015 IFIP International Federation for Information Processing

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Driff, L.N., Berkani, L., Guessoum, A., Bendjahel, A. (2015). Social Validation of Solutions in the Context of Online Communities. In: Amine, A., Bellatreche, L., Elberrichi, Z., Neuhold, E., Wrembel, R. (eds) Computer Science and Its Applications. CIIA 2015. IFIP Advances in Information and Communication Technology, vol 456. Springer, Cham. https://doi.org/10.1007/978-3-319-19578-0_8

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  • DOI: https://doi.org/10.1007/978-3-319-19578-0_8

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19577-3

  • Online ISBN: 978-3-319-19578-0

  • eBook Packages: Computer ScienceComputer Science (R0)