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MOOC Resources Recommendation Based on Heterogeneous Information Network

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Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD 2022)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 153))

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Abstract

Aiming at the problem that the existing MOOC recommendation mechanism cannot meet the dynamic and diversified learning needs of different individuals, a MOOC resource recommendation model based on heterogeneous information network is proposed. First by capturing MOOC platform of the heterogeneity between multiple entities in building its corresponding heterogeneous information network, and then through the node level attention and meta-path level fusion of attention, will learn to the user and the knowledge incorporated into the extended matrix factorization framework, to predict user preferences for knowledge, to carry on the personalized recommendation service. Experimental results show that this model has better recommendation performance than other commonly used models, and effectively solves the problem of personalized recommendation for learners.

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Acknowledgement

This research was supported by the Key R&D Project of Shaanxi Province (Grant No.2020GY-010), the key project of Shaanxi Education reform (Grant No. 21BG038).

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Authors and Affiliations

  1. Xi’an University of Posts and Telecommunications, Xi’an, 710121, Shaanxi, China

    Shuyan Wang, Wei Wu & Yanyan Zhang

Authors
  1. Shuyan Wang
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  2. Wei Wu
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  3. Yanyan Zhang
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Corresponding author

Correspondence to Wei Wu .

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Editors and Affiliations

  1. Division of Intelligent Future Technologies, Mälardalen University, Västerås, Västmanlands Län, Sweden

    Ning Xiong

  2. Department of Electronic and Computer Engineering, Brunel University London, Uxbridge, Middlesex, UK

    Maozhen Li

  3. School of Information Science and Technology, Hunan University, Changsha, Hunan, China

    Kenli Li

  4. School of Information Science and Technology, Hunan University, Changsha, Hunan, China

    Zheng Xiao

  5. College of Computer and Data Science, Fuzhou University, Fuzhou, Fujian, China

    Longlong Liao

  6. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Lipo Wang

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Wang, S., Wu, W., Zhang, Y. (2023). MOOC Resources Recommendation Based on Heterogeneous Information Network. In: Xiong, N., Li, M., Li, K., Xiao, Z., Liao, L., Wang, L. (eds) Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. ICNC-FSKD 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 153. Springer, Cham. https://doi.org/10.1007/978-3-031-20738-9_132

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