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Recommendation Algorithm Based on Wide&Deep and FM

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Proceedings of International Conference on Artificial Intelligence and Communication Technologies (ICAICT 2023) (ICAICT 2023)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 368))

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Abstract

Online learning is more and more popular because it is not limited by time and space. How to choose a suitable course from thousands of online courses is a great challenge faced by online learners, and online course recommendation came into being. The personalized recommendation algorithm analyzes the user’s preferences by collecting some previous historical records of the user and other information, and generates recommendations for the user. Since Wide&Deep was proposed, due to its inherent ease of implementation, adaptability, and versatility, this approach has gained significant traction across various industry sectors. But its feature intersection method is not efficient. Sufficient feature engineering is required to provide informative features that can effectively distinguish objects. In this paper, the WD-FM model is proposed by combining Wide&Deep and factorization machine, and good results have been achieved through experimental demonstration.

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Author information

Authors and Affiliations

  1. Shenyang Institute of Computing Technology, Chinese Academy of Sciences, Shenyang, China

    Songkun Zheng, Xian Li & Xueliang Chen

  2. University of Chinese Academy of Sciences, Beijing, China

    Songkun Zheng, Xian Li & Xueliang Chen

  3. Beijing Zhongke Zhihe Digital Technology Co., Ltd., Beijing, China

    Xu Li

Authors
  1. Songkun Zheng
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  2. Xian Li
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  3. Xueliang Chen
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  4. Xu Li
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Corresponding author

Correspondence to Xu Li .

Editor information

Editors and Affiliations

  1. Technical University of Sofia, Sofia, Bulgaria

    Roumen Kountchev

  2. Interscience Institute of Management and Technology, Bhubaneswar, Odisha, India

    Srikanta Patnaik

  3. University of Hyogo, Kobe, Japan

    Kazumi Nakamatsu

  4. TK Engineering, Sofia, Bulgaria

    Roumiana Kountcheva

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Zheng, S., Li, X., Chen, X., Li, X. (2024). Recommendation Algorithm Based on Wide&Deep and FM. In: Kountchev, R., Patnaik, S., Nakamatsu, K., Kountcheva, R. (eds) Proceedings of International Conference on Artificial Intelligence and Communication Technologies (ICAICT 2023). ICAICT 2023. Smart Innovation, Systems and Technologies, vol 368. Springer, Singapore. https://doi.org/10.1007/978-981-99-6641-7_17

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  • DOI: https://doi.org/10.1007/978-981-99-6641-7_17

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-6640-0

  • Online ISBN: 978-981-99-6641-7

  • eBook Packages: EngineeringEngineering (R0)

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