HieRec: Hierarchical User Interest Modeling for Personalized News Recommendation

Tao Qi; Fangzhao Wu; Chuhan Wu; Peiru Yang; Yang Yu; Xing Xie; Yongfeng Huang

doi:10.18653/v1/2021.acl-long.423

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JOURNAL ARTICLE

HieRec: Hierarchical User Interest Modeling for Personalized News Recommendation

Tao Qi Fangzhao Wu Chuhan Wu Peiru Yang Yang Yu Xing Xie Yongfeng Huang

Year: 2021 Pages: 5446-5456

DOI: 10.18653/v1/2021.acl-long.423

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Abstract

Tao Qi, Fangzhao Wu, Chuhan Wu, Peiru Yang, Yang Yu, Xing Xie, Yongfeng Huang. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). 2021.

Keywords:

Computer science Computational linguistics Association (psychology) Joint (building) World Wide Web Natural language processing Information retrieval Artificial intelligence Engineering Philosophy

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17.18

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0.99

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Topics

Recommender Systems and Techniques

Physical Sciences → Computer Science → Information Systems

Topic Modeling

Physical Sciences → Computer Science → Artificial Intelligence

Advanced Graph Neural Networks

Physical Sciences → Computer Science → Artificial Intelligence

HieRec: Hierarchical User Interest Modeling for Personalized News Recommendation

Abstract

Metrics

Citation History

Topics

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