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A Semantic Recommender System for iDTV Based on Educational Competencies

  • Diego DuranEmail author
  • Gabriel Chanchí
  • Jose Luis Arciniegas
  • Sandra Baldassarri
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 689)

Abstract

Interactive Digital Television (iDTV) provides a large amount of educational programs useful for supporting students’ learning and teaching processes. Nevertheless, despite the continuous growth of the number of available contents, it is hard to find those which can be useful for a specific educational purpose. In order to provide a solution to this issue, in this paper we propose a model of a semantic Recommender System for educational iDTV programs, in which, the concept of competency and its features have been integrated as contextual information to enhance both the user and program information. Thus, we can establish filtering strategies in accordance with educational requirements. Furthermore, this proposal incorporates ontology-based filtering to enhance the inference capacity of another approaches, such as, content-based, collaborative, and syntactic matching.

Keywords

Educational competency Metadata Recommender system Semantics Interactive digital television 

Notes

Acknowledgements

This work is supported by the National Doctorates program, call with reference number 617-2013 of Colciencias, the UsabiliTV project supported by Colciencias with ID 1103 521 2846 and the Asociación Universitaria Iberoamericana de Postgrado (AUIP). Also, this work is partially supported by the Government of Spain, contract TIN2015-67149-C3-1R and the RedAUTI project (Red temática en Aplicaciones y Usabilidad de la Television Digital Interactiva), CYTED 512RT0461.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Universidad del CaucaPopayanColombia
  2. 2.Institución Universitaria Colegio Mayor del CaucaPopayanColombia
  3. 3.Universidad de ZaragozaSaragossaSpain

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