Prerequisite-aware Recommendation
Prerequisite-Aware Recommendation is a type of recommender system approach that explicitly incorporates prerequisite relationships among learning resources to ensure recommended items are both relevant and sequenced appropriately according to the learner's current knowledge level.
15
Publications
554
Citations
48
Authors
23
Institutions
Publications per year
2017–2026
10
15
Goal-based Course Recommendation
Weijie Jiang, Zachary A. Pardos, Qiang Wei · 2019 · 119 citations · Full text
Inferring Concept Prerequisite Relations from Online Educational Resources
Sudeshna Roy, Meghana Madhyastha, Sheril Lawrence et al. · 2019 · 63 citations · Full text
Semi-Supervised Techniques for Mining Learning Outcomes and Prerequisites
Igor Labutov, Yun Huang, Peter Brusilovsky et al. · 2017 · 32 citations · Full text
1–5 of 15
48
2
h-index
2
h-index
2
h-index
2
h-index
2
h-index
1–5 of 48
23
Stanford University
Stanford, United States
2 h-index
5 publications
155 citations
Guangxi University
Nanning, China
2 h-index
8 publications
180 citations
National University of Singapore
Singapore, Singapore
1 h-index
1 publications
63 citations
Shanghai Polytechnic University
Shanghai, China
1 h-index
3 publications
69 citations
University of California, Berkeley
Berkeley, United States
1 h-index
2 publications
238 citations
Carnegie Mellon University
Pittsburgh, United States
1 h-index
1 publications
32 citations
Tsinghua University
Beijing, China
1 h-index
1 publications
119 citations
JK Lakshmipat University
Jaipur, India
1 h-index
1 publications
10 citations
1–8 of 23
TOMCCAP · 1 publications · 24 citations
1
h-index
1 publications · 104 citations
1
h-index
1 publications · 23 citations
1
h-index
1 publications · 19 citations
1
h-index
IJMSO · 1 publications · 10 citations
1
h-index
1–5