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A fine-grained and multi-context-aware learning path recommendation model over knowledge graphs for online learning communities

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成果类型:
期刊论文
作者:
Zhang, Si;Hui, Ning;Zhai, Peiyun;Xu, Jiali;Cao, Lanying;...
通讯作者:
Zhang, S
作者机构:
[Hui, Ning; Cao, Lanying; Zhang, Si; Zhai, Peiyun; Xu, Jiali] Cent China Normal Univ, Fac Artificial Intelligence Educ, Hubei Res Ctr Educ Informationizat, Wuhan 430079, Peoples R China.
[Wang, Qiyun] Nanyang Technol Univ, Natl Inst Educ, 1 Nanyang Walk, Singapore, Singapore.
通讯机构:
[Zhang, S ] C
Cent China Normal Univ, Fac Artificial Intelligence Educ, Hubei Res Ctr Educ Informationizat, Wuhan 430079, Peoples R China.
语种:
英文
关键词:
Knowledge graph;Learning path recommendation;Online learning community;User recommendation
期刊:
Information Processing & Management
ISSN:
0306-4573
年:
2023
卷:
60
期:
5
页码:
103464
基金类别:
This work was supported by a project funded by the National Natural Science Foundation of China (No. 62077016 ). This work was conducted as part of a Research Project Supported by the Fundamental Research Funds for the Central Universities (Grant Number CCNU22QN013 ). This work was also conducted as part of a Research Project for Construction of National Teacher Development and Collaborative Innovation Experimental Base in Central China Normal University (Grant Number CCNUTEIII 2021-22 ).
机构署名:
本校为第一且通讯机构
摘要:
Existing approaches to learning path recommendation for online learning communities mainly rely on the individual characteristics of users or the historical records of their learning processes, but pay less attention to the semantics of users’ postings and the context. To facilitate the knowledge understanding and personalized learning of users in online learning communities, it is necessary to conduct a fine-grained analysis of user data to capture their dynamical learning characteristics and potential knowledge levels, so as to recommend app...

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