Domain-Aware Grade Prediction and Top-n Course Recommendation-Reference-Cited by-同舟云学术

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Domain-Aware Grade Prediction and Top-n Course Recommendation

Published:2016-09-07 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 10th ACM Conference on Recommender Systems
language:
Short-container-title:

Author:

Elbadrawy Asmaa¹,Karypis George¹

Affiliation:

1. University of Minnesota, Minneapolis, USA

Funder

NSF

Army Research Office

the Digital Technology Center at the University of Min- nesota

Intel Software and Services Group

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/2959100.2959133

Reference28 articles.

1. Incorporating contextual information in recommender systems using a multidimensional approach

2. Regression-based latent factor models

3. Localized factor models for multi-context recommendation

4. Matrix factorization techniques for context aware recommendation

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1. Ensemble Machine Learning One-Versus-Rest Multilevel Grade Classification and Prediction;Lecture Notes in Networks and Systems;2024

2. A Survey on Explainable Course Recommendation Systems;Lecture Notes in Computer Science;2024

3. SCA Advice System: Ontology Framework for a Computer Curricula Advice System Based on Student Behavior;Journal of information and communication convergence engineering;2023-12-31

4. Knowledge-aware reasoning with self-supervised reinforcement learning for explainable recommendation in MOOCs;Neural Computing and Applications;2023-12-10

5. A Systematic Review on Predicting the Performance of Students in Higher Education in Offline Mode Using Machine Learning Techniques;Wireless Personal Communications;2023-12

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