The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Sep. 19, 2023
Filed:
Jul. 31, 2020
Tencent Technology (Shenzhen) Company Limited, Shenzhen, CN;
Yi Liu, Guangdong, CN;
Lantao Hu, Guangdong, CN;
Bo Zhang, Guangdong, CN;
Feng Xia, Guangdong, CN;
Leyu Lin, Guangdong, CN;
Zhe Feng, Guangdong, CN;
Lei Chen, Guangdong, CN;
Jun Rao, Guangdong, CN;
Shukai Liu, Guangdong, CN;
Zhijie Qiu, Guangdong, CN;
Zhenlong Sun, Guangdong, CN;
Liangdong Wang, Guangdong, CN;
Tencent Technology (Shenzhen) Company Limited, Shenzhen, CN;
Abstract
This application provides an article recommendation method and apparatus, a computer device, and a storage medium. The method includes: obtaining a historical reading article set of a to-be-analyzed target user, the historical reading article set comprising a plurality of historical articles that have been read by the target user at different reading moments; determining, for each historical article of the plurality of historical articles, first attention degree values between the each historical article and candidate reference historical articles having reading moments before that of the each historical article, the first attention degree values reflecting a possibility that a user is recommended to read the historical article if the user has read the candidate reference historical articles; selecting at least one recommendation reference article from the candidate reference historical articles corresponding to the historical articles according to the first attention degree values between the historical articles and corresponding candidate reference historical articles; and determining, in a recommendable article set at least one candidate recommended article to be recommended to the target user based on the at least one recommendation reference article.