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Exploiting high-order local and global user-item interactions for effective recommendation

KNOWLEDGE-BASED SYSTEMS (2022)

A text GAN framework for creative essay recommendation

Guoxi Liang et al.

Summary: Automated essay scoring is an exciting task in natural language processing where researchers have been exploring the detection of creative essays. This paper proposes a method using a generative adversarial network framework to judge the creativity of essays by masking part of the content. Experimental results show the feasibility of the proposed approach in identifying creative essays.

KNOWLEDGE-BASED SYSTEMS (2021)

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Article Computer Science, Artificial Intelligence

Adaptive course recommendation in MOOCs

Yuanguo Lin et al.

Summary: This paper introduces a novel course recommendation framework named DARL, which aims to enhance the adaptivity of the recommendation model by automatically capturing users' dynamic interests and adaptively updating the attention weight of courses to improve recommendation accuracy. Empirical experiments on two real-world MOOCs datasets show that DARL significantly outperforms state-of-the-art course recommendation methods in major evaluation metrics.

KNOWLEDGE-BASED SYSTEMS (2021)

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Article Computer Science, Artificial Intelligence