Learning Resource Recommendation: An Orchestration of Content-Based Filtering, Word Semantic Similarity and Page Ranking

Chan Nguyen Ngoc 1 Azim Roussanaly 1 Anne Boyer 1
1 KIWI - Knowledge Information and Web Intelligence
LORIA - AIS - Department of Complex Systems, Artificial Intelligence & Robotics
Abstract : Technologies supporting online education have been abun-dantly developed recent years. Many repositories of digital learning re-sources have been set up and many recommendation approaches have been proposed to facilitate the consummation of learning resources. In this paper, we present an approach that combines three recommendation technologies: content-based filtering, word semantic similarity and page ranking to make resource recommendations. Content-based filtering is applied to filter syntactically learning resources that are similar to user profile. Word semantic similarity is applied to consolidate the content-based filtering with word semantic meanings. Page ranking is applied to identify the importance of each resource according to its relations to others. Finally, a hybrid approach that orchestrates these techniques has been proposed. We performed several experiments on a public learning resource dataset. Results on similarity values, coverage of recommenda-tions and computation time show that our approach is feasible.
Keywords : Learning Resource Technology Enhanced Learning Content- based Filtering Word Semantic Similarity TF-IDF VSM PageRank
Type de document :
Communication dans un congrès
EC-TEL 2014 : 9th European Conference on Technology Enhanced Learning, Sep 2014, Gratz, Austria. Springer, Lecture Notes in Computer Science, pp.302-316, 2014, Open Learning and Teaching in Educational Communities. 〈10.1007/978-3-319-11200-8_23〉
Liste complète des métadonnées

Littérature citée [22 références]  Voir  Masquer  Télécharger
https://hal.inria.fr/hal-01109258
Contributeur : Azim Roussanaly <>
Soumis le : dimanche 25 janvier 2015 - 20:12:14
Dernière modification le : samedi 17 novembre 2018 - 12:12:02
Document(s) archivé(s) le : dimanche 26 avril 2015 - 10:11:01

Fichier

2014 ECTEL.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

INRIA | UNIV-LORRAINE | LORIA-AIS | LORIA

Citation

Chan Nguyen Ngoc, Azim Roussanaly, Anne Boyer. Learning Resource Recommendation: An Orchestration of Content-Based Filtering, Word Semantic Similarity and Page Ranking. EC-TEL 2014 : 9th European Conference on Technology Enhanced Learning, Sep 2014, Gratz, Austria. Springer, Lecture Notes in Computer Science, pp.302-316, 2014, Open Learning and Teaching in Educational Communities. 〈10.1007/978-3-319-11200-8_23〉. 〈hal-01109258〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

352

Téléchargements de fichiers

127

Contact


archive-ouverte@inria.fr