Apr 8, 2022 · In this paper, we are motivated to propose a Knowledge-Enhanced Multi-task Learning model for Course Recomme-ndation (KMCR), which regards the improved ...
Apr 11, 2022 · In this paper, we are motivated to propose a Knowledge-Enhanced Multi-task Learning model for Course Recomme-ndation (KMCR), which regards the improved ...
Knowledge tracing (KT) aims to model learners' knowledge level and predict future performance given their past interactions in learning applications.
Mar 2, 2023 · The second is how to deal with datasets with different sparsity. Tackling these challenging issues, this paper proposes an enhanced MKR (EMKR) ...
May 14, 2021 · This paper proposes the Ripp-MKR model, a multitask feature learning approach for knowledge graph enhanced recommendations with RippleNet.
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Jan 23, 2019 · ABSTRACT. Collaborative filtering often suffers from sparsity and cold start problems in real recommendation scenarios, therefore, ...
3 days ago · KT models student knowledge based on prior performance with learning materials, while BM focuses on patterns such as student preferences, ...
Jun 9, 2023 · We demonstrate the advantage of combining knowledge graph enhancement with previous multi-domain recom- mendation techniques to provide better ...
Oct 12, 2023 · To tackle this problem, we propose a novel knowledge-enhanced multi-task recommendation algorithm in hyperbolic space named KMRH. The algorithm ...
Missing: Course | Show results with:Course
Aug 15, 2024 · We propose a novel method named Knowledge-Enhanced Multi-Task Parallelized Recommendation Algorithm Incorporating Attention-Embedded Propagation (KMPR-AEP).