Recommendation Fusion Model Based on LSTM and Deep Matrix Factorization

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- Recommendation Fusion Model Based on LSTM and Deep Matrix Factorization
- “在推荐系统领域，研究者提出了LFDMF模型，通过LSTM和深度矩阵分解，有效提升了推荐准确性。”
- Software Guide Vol. 23, Issue 9, Pages: 41-47(2024)
- 作者机构：
  
  1.江西理工大学理学院,江西赣州 341000
  2.嘉兴南湖学院图书馆,浙江嘉兴 314001
  3.浙江省医学电子与数字健康重点实验室,浙江嘉兴 314000
- 作者简介：
- 基金信息：
- DOI：10.11907/rjdk.231826
  CLC： TP391.3
- Published：16 September 2024，
  
  Received：19 September 2023，
- 稿件说明：
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丁伟健,卢敏,杨忠明等.基于LSTM与深度矩阵分解的推荐融合模型[J].软件导刊,2024,23(09):41-47.

DING Weijian,LU Min,YANG Zhongming,et al.Recommendation Fusion Model Based on LSTM and Deep Matrix Factorization[J].Software Guide,2024,23(09):41-47.
丁伟健,卢敏,杨忠明等.基于LSTM与深度矩阵分解的推荐融合模型[J].软件导刊,2024,23(09):41-47. DOI： 10.11907/rjdk.231826.

DING Weijian,LU Min,YANG Zhongming,et al.Recommendation Fusion Model Based on LSTM and Deep Matrix Factorization[J].Software Guide,2024,23(09):41-47. DOI： 10.11907/rjdk.231826.

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