Personalized exercise recommendation algorithm combining learning objective and assignment feedback

Xia, Jiali; Li, Guangquan; Cao, Zhang

doi:10.3233/jifs-169652

Cited by 20 publications

(11 citation statements)

References 15 publications

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“…e algorithm adds consideration of system characteristics, project characteristics, and user characteristics. e Biased-SVD scoring model is as follows [19]:…”

Section: Recommendation Algorithm Based On Matrix Factorizationmentioning

confidence: 99%

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Knowledge-Based Intelligent Education Recommendation System with IoT Networks

Xin

Shi

Sohail

2022

Security and Communication Networks

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The intelligent education recommendation system can recommend knowledge suitable for students' personal learning. However, the traditional recommendation algorithm has generality problems, which lead to poor knowledge recommendation effects. In order to improve the performance of the education recommendation system, based on the machine learning algorithm, this paper combines the knowledge graph algorithm to improve the recommendation algorithm and decomposes the matrix with a higher dimension into several matrices with relatively small dimensions through matrix transformation. Moreover, this paper conducts in-depth mining of the potential attributes of users and items and improves the matrix decomposition formula based on knowledge recommendation requirements. In addition, this paper constructs the framework of the intelligent education recommendation system with IoT networks based on the analysis of functional requirements. Finally, this paper designs experiments to verify and analyze the model from the perspective of model performance and user satisfaction. The research results show that the algorithm model constructed in this paper is effective.

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“…e algorithm adds consideration of system characteristics, project characteristics, and user characteristics. e Biased-SVD scoring model is as follows [19]:…”

Section: Recommendation Algorithm Based On Matrix Factorizationmentioning

confidence: 99%

“…d SV D + + is a dual model of SV D + +, that is, matrix decomposition based on implicit user feedback. e d SV D + + scoring model is as follows [19]:…”

Section: Recommendation Algorithm Based On Matrix Factorizationmentioning

confidence: 99%

Knowledge-Based Intelligent Education Recommendation System with IoT Networks

Xin

Shi

Sohail

2022

Security and Communication Networks

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show abstract

“…, and then r ij ' ∈ [0, 1] . Of course, the above translation range transformation can also be used [19].…”

Section: Similarity Coefficient Methodsmentioning

confidence: 99%

Research on the Fusion of Hybrid Fuzzy Clustering Algorithm and Computer Automatic Test Paper Composition Algorithm

Kan

2022

Advances in Multimedia

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In order to improve the effect of intelligent automatic test paper composition, this paper combines the hybrid fuzzy clustering algorithm to study the computer automatic test paper composition algorithm. In this paper, a computer automatic test paper composition system based on hybrid fuzzy clustering algorithm is constructed. Moreover, the hybrid fuzzy clustering method used in this paper is used as the basic algorithm of the system, and the algorithm is improved according to the actual needs of intelligent paper composition. In addition, this paper uses an intelligent algorithm to input the relevant constraint parameters and combines the original parameters to select the most suitable test questions from the database and combine them into test papers. Finally, this paper constructs the system structure based on the requirements of intelligent test paper composition. The experimental research shows that the computer automatic test paper composition system based on the hybrid fuzzy clustering algorithm proposed in this paper has a good test paper composition function, which can effectively promote the progress of the intelligent examination mode in colleges and universities.

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“…e sample set x 1 , x 2 , ..., x N 􏼈 􏼉 of the input space is mapped into the feature space and becomes 4 Scientific Programming Φ(x 1 ), Φ(x 2 ), ..., Φ(x N ) 􏼈 􏼉. en, the distance (kernel distance) of the sample points xi, xj in the feature space is [22]…”

Section: Internet Of Things Learning Methodsmentioning

confidence: 99%

IoT-Assisted Hybrid Intelligent Learning Architecture Based on Digital Education in a Diverse Society

2021

Scientific Programming

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The existing research paradigm has caused the research of educational theory to be criticized for lack of logic and scientificity. With the gradual deepening and refinement of the development of smart education platforms, the educational process can be quantified, and the research paradigm of educational science has moved from a sampling model to a full-sample model, and it has become a real empirical science. This paper combines the Internet of Things technology to construct a hybrid intelligent learning system and applies it to digital education in a diverse society to construct a functional structure of the extraction system. Moreover, starting from the actual situation of intelligent education, this paper combines a simulation system to implement an IoT-assisted hybrid intelligent learning architecture and evaluates the teaching effect of the system. Through experimental research, it can be known that the IoT-assisted hybrid intelligent learning framework based on social diversified digital education has certain effects and has a certain reference effect for the development of subsequent intelligent education.

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Personalized exercise recommendation algorithm combining learning objective and assignment feedback

Cited by 20 publications

References 15 publications

Knowledge-Based Intelligent Education Recommendation System with IoT Networks

Knowledge-Based Intelligent Education Recommendation System with IoT Networks

Research on the Fusion of Hybrid Fuzzy Clustering Algorithm and Computer Automatic Test Paper Composition Algorithm

IoT-Assisted Hybrid Intelligent Learning Architecture Based on Digital Education in a Diverse Society

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