2015 | OriginalPaper | Buchkapitel
Contextual Recommendation of Educational Contents
verfasst von : Nidhi Saraswat, Hiranmay Ghosh, Mohit Agrawal, Uma Narayanan
Erschienen in: Artificial Intelligence in Education
Aktivieren Sie unsere intelligente Suche um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
This paper proposes a recommendation engine for educational contents in the organizational context of a user. The novelty in this paper lies in creating a context model for a user incorporating the role and the tasks assigned to him, and its application to recommendation problem. The recommendations are made on the basis of the estimated gap that exists between an employee’s current knowledge level and the skill-set required in his job-context. A probabilistic reasoning framework is used for recommendations, to account for the inexact specifications of user competencies and requirements of the job context.