Name
Title | ||
|---|---|---|
A Heuristic Approach For New-Item Cold Start Problem In Recommendation Of Micro Open Education Resources |
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. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-319-91464-0_21 | INTELLIGENT TUTORING SYSTEMS, ITS 2018 |
Keywords | Field | DocType |
Cold start, Open Education Resources, Adaptive micro learning, Heuristic recommendation, Learning path | Heuristic,Open education,Information retrieval,Cold start,Computer science,Online computation,Artificial intelligence,Cold start (automotive),Machine learning,Empirical research | Conference |
Volume | ISSN | Citations |
10858 | 0302-9743 | 2 |
PageRank | References | Authors |
0.39 | 10 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Geng Sun | 1 | 61 | 10.04 |
| Tingru Cui | 2 | 40 | 14.12 |
| Dongming Xu | 3 | 448 | 35.20 |
| Jun Shen | 4 | 234 | 40.40 |
| Shiping Chen | 5 | 20 | 7.52 |