A Dynamic Personalized News Recommendation System Based on BAP User Profiling Method | Zendy

Zhiliang Zhu | Zendy; Deyang Li | Zendy; Jie Liang | Zendy; Guoqi Liu | Zendy; Hai Yu | Zendy

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A Dynamic Personalized News Recommendation System Based on BAP User Profiling Method

Author(s) -

Zhiliang Zhu,

Deyang Li,

Jie Liang,

Guoqi Liu,

Hai Yu

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2858564

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

In this paper, we propose a user profile model to describe users' preferences from multiple perspectives. Then, we discuss the degree of the user's preferences for historical news, and propose a method to calculate the preference weight of historical news according to the user's reading behavior and the popularity of news. This method could construct user profiles more accurately. Besides, we provide a dynamic method for news recommendation, in which both short-term and long-term user preferences are considered. The experimental results indicate that our method can significantly improve the recommendation effect.

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