A Heuristic Approach for New-item Cold Start Problem in Recommendation of Micro Open Education Resources

Authors

Geng Sun, University of WollongongFollow
Tingru Cui, University of WollongongFollow
Dongming Xu, University of QueenslandFollow
Jun Shen, University of WollongongFollow
Shiping Chen, CSIRO ICT CentreFollow

RIS ID

119987

Publication Details

Sun, G., Cui, T., Xu, D., Shen, J. & Chen, S. (2018). A Heuristic Approach for New-item Cold Start Problem in Recommendation of Micro Open Education Resources. Lecture Notes in Computer Science, 10858 212-222. Montreal 14th International Conference on Intelligent Tutoring Systems

Abstract

The recommendation of micro Open Education Resources (OERs) suffers from the new-item cold start problem because little is known about the continuously published micro OERs. This paper provides a heuristic approach to inserting newly published micro OERs into established learning paths, to enhance the possibilities of new items to be discovered and appear in the recommendation lists. It considers the accumulation and attenuation of user interests and conform with the demand of fast response in online computation. Performance of this approach has been proved by empirical studies.

Grant Number

ARC/DP180101051