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一个基于切换的深度学习框架,用于个性化和适应性的电子商务建议

Kapil Saini1, Ajmer Singh2, Manoj Diwakar3,4

  • 1School of Computer Science and Engineering, Geeta University, Panipat, Haryana, 132145, India.

Scientific reports
|February 24, 2026
PubMed
概括

本研究引入了一种基于切换的新型混合推系统,以有效处理各种用户配置文件和跨领域的建议. 该系统显著提高了不同用户群体的推准确性和性能,解决了数据稀疏性和实时适应性等挑战.

关键词:
跨领域的建议.不同的用户配置文件.多任务学习是多任务学习.推系统是推系统.基于开关的混合型模型.

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