Recommending multimedia educational resources on the moving platform

Iacopo Vagliano, Sibgha Nazir

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

2 Citations (Scopus)

Abstract

The MOVING platform includes a huge amount of heterogeneous educational resources, such as documents, videos, and social media posts. We show how the MOVING recommender system can support users in dealing with such a massive information flow by leveraging semantic profiling. The HCF-IDF model exploits a thesaurus or ontology to represents users and documents and it is used to recommend educational resources based on users’ search history. We describe how the recommender is implemented how it is applied to the MOVING platform to deal with the huge amount of resources stored in the platform, their variety and the increasing number of users.

Original languageEnglish
Title of host publication8th International Workshop on Bibliometric-Enhanced Information Retrieval, BIR 2019
Pages148-158
Number of pages11
Volume2345
Publication statusPublished - 2019
Externally publishedYes
Event8th International Workshop on Bibliometric-Enhanced Information Retrieval, BIR 2019 - Cologne, Germany
Duration: 14 Apr 2019 → …

Publication series

NameCEUR Workshop Proceedings
PublisherCEUR-WS

Conference

Conference8th International Workshop on Bibliometric-Enhanced Information Retrieval, BIR 2019
Country/TerritoryGermany
CityCologne
Period14/04/2019 → …

Keywords

  • Multimedia content recommendation
  • Recommender systems
  • Semantic profiling
  • Technology-enhanced learning

Cite this