An Intelligent Exercise Recommendation System Combining AIGC and Knowledge Graphs

Lizhu Le

doi:10.47297/taposatWSP2633-456922.20250601

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An Intelligent Exercise Recommendation System Combining AIGC and Knowledge Graphs

Volume 6, Issue 1

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An Intelligent Exercise Recommendation System Combining AIGC and Knowledge Graphs
An Intelligent Exercise Recommendation System Combining AIGC and Knowledge Graphs
University of Perpetual Help System DALTA , Las Pinas Campus: Alabang-Zapote Road, Pamplona 3,Las Pinas City,1740 Philippines
Vol. 6, Issue 1, Pages: 115-119(2025)
Published：21 January 2025
DOI：10.47297/taposatWSP2633-456922.20250601
Accepted：

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Le Lizhu.An Intelligent Exercise Recommendation System Combining AIGC and Knowledge Graphs[J].Theory and Practice of Science and Technology,2025,06(01):115-119.
DOI：

Le Lizhu.An Intelligent Exercise Recommendation System Combining AIGC and Knowledge Graphs[J].Theory and Practice of Science and Technology,2025,06(01):115-119. DOI： 10.47297/taposatWSP2633-456922.20250601.

摘要

Abstract

This paper focuses on an intelligent exercise recommendation system combining AIGC and knowledge graph technology. This system uses the advantages of natural language processing and machine learning of AIGC technology

and combines the rich entity relationship network of knowledge graph to realize the accurate capture of students' learning needs and intelligent recommendation of personalized exercises. Through in-depth analysis of students' learning behavior

interest preference and knowledge mastery

the system can generate exercises that meet students' ability level and learning goals and provide detailed analysis and feedback

so as to effectively promote students' learning progress and personalized development. This paper aims to discuss the design and implementation of the system

as well as its application prospects and potential value in the field of education.

关键词

Keywords

references

Zhang G ,Xiong J Y ,Hu P J , et al.Triplet trustworthiness validation with knowledge graph reasoning[J].Engineering Applications of Artificial Intelligence,2025,141109813-109813.

Wang J ,Li P ,Liu Y , et al.Risk identification of listed companies violation by integrating knowledge graph and multi-source risk factors[J].Engineering Applications of Artificial Intelligence,2025,141109774-109774.

Shim M ,Choi H ,Koo H , et al.OmEGa([formula omitted]): Ontology-based information extraction framework for constructing task-centric knowledge graph from manufacturing documents with large language model[J].Advanced Engineering Informatics,2025,64103001-103001.

Haruna U E ,Asiedu K W ,Bello O L .Mapping the knowledge domain of natural capital and sustainability: A bibliometric analysis using the Scopus database for future research direction[J].Development and Sustainability in Economics and Finance,2025,5100035-100035.

Li J ,Zhang J ,Wang L , et al.A Hierarchical Spatiotemporal Data Model Based on Knowledge Graphs for Representation and Modeling of Dynamic Landslide Scenes[J].Sustainability,2024,16(23):10271-10271.

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