Shoujian Yu¹, Zhenchi Jie¹, Guowen Wu¹, Hong Zhang¹, Shigen Shen^2,*

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1729-1751, 2023, DOI:10.32604/iasc.2023.039911

Abstract In recent years, the type and quantity of news are growing rapidly, and it is not easy for users to find the news they are interested in the massive amount of news. A news recommendation system can score and predict the candidate news, and finally recommend the news with high scores to users. However, existing user models usually only consider users’ long-term interests and ignore users’ recent interests, which affects users’ usage experience. Therefore, this paper introduces gated recurrent unit (GRU) sequence network to capture users’ short-term interests and combines users’ short-term interests and long-term interests to characterize users. While… More >

Kehua Yang^{1, *}, Shaosong Long¹, Wei Zhang¹, Jiqing Yao², Jing Liu¹

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 557-570, 2020, DOI:10.32604/cmc.2020.09907

Abstract The personalized news recommendation has been very popular in the news recommendation field. In most research, the picture information in the news is ignored, but the information conveyed to the users through pictures is more intuitive and more likely to affect the users’ reading interests than the one in the textual form. Therefore, in this paper, a model that combines images and texts in the news is proposed. In this model, the new tags are extracted from the images and texts in the news, and based on these new tags, an adaptive tag (AT) algorithm is proposed. The AT algorithm… More >