Towards Massive Data and Sparse Data in Adaptive Micro Open Educational Resource Recommendation: A Study on Semantic Knowledge Base Construction and Cold Start Problem

Authors

Geng Sun, University of WollongongFollow
Tingru Cui, University of WollongongFollow
Ghassan Beydoun, University of WollongongFollow
Shiping Chen, CSIRO ICT CentreFollow
Fang Dong, Southeast UniversityFollow
Dongming Xu, University of QueenslandFollow
Jun Shen, University of WollongongFollow

RIS ID

113086

Publication Details

Sun, G., Cui, T., Beydoun, G., Chen, S., Dong, F., Xu, D. & Shen, J. (2017). Towards Massive Data and Sparse Data in Adaptive Micro Open Educational Resource Recommendation: A Study on Semantic Knowledge Base Construction and Cold Start Problem. Sustainability, 9 (6), 898-1-898-21.

Abstract

Micro Learning through open educational resources (OERs) is becoming increasingly popular. However, adaptive micro learning support remains inadequate by current OER platforms. To address this, our smart system, Micro Learning as a Service (MLaaS), aims to deliver personalized OER with micro learning to satisfy their real-time needs.