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Deep Adaptive Interest Network: Personalized Recommendation with Context-Aware Learning

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DOI: 10.23977/jeis.2024.090315 | Downloads: 12 | Views: 273

Author(s)

Shuaishuai Huang 1, Haowei Yang 2, You Yao 3, Xueting Lin 4, Yuming Tu 5

Affiliation(s)

1 Department of Software, University of Science and Technology of China, Hefei, Anhui, China
2 Cullen College of Engineering, University of Houston, Houston, TX, USA
3 Viterbi School of Enigneering, University of Southern California, Los Angeles, California, USA
4 Department of Electrical Engineering and Information Systems, University of Tokyo, Tokyo, Japan
5 Independent Researcher, New York, USA

Corresponding Author

Shuaishuai Huang

ABSTRACT

In personalized recommendation systems, accurately capturing users' evolving interests and combining them with contextual information is a critical research area. This paper proposes a novel model called the Deep Adaptive Interest Network (DAIN), which dynamically models users' interests while incorporating context-aware learning mechanisms to achieve precise and adaptive personalized recommendations. DAIN leverages deep learning techniques to build an adaptive interest network structure that can capture users' interest changes in real-time while further optimizing recommendation results by integrating contextual information. Experiments conducted on several public datasets demonstrate that DAIN excels in both recommendation performance and computational efficiency. This research not only provides a new solution for personalized recommendation systems but also offers fresh insights into the application of context-aware learning in recommendation systems.

KEYWORDS

Personalized Recommendation Systems, Deep Learning, User Interest Modeling, Context-Aware Learning

CITE THIS PAPER

Shuaishuai Huang, Haowei Yang, You Yao, Xueting Lin, Yuming Tu, Deep Adaptive Interest Network: Personalized Recommendation with Context-Aware Learning. Journal of Electronics and Information Science (2024) Vol. 9: 105-115. DOI: http://dx.doi.org/10.23977/10.23977/jeis.2024.090315.

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