Overview of research on news recommendation algorithms
With the vigorous development of the Internet,many online news are constantly generated,which leads to news in-formation overload.It is difficult for readers to find the content they are interested in in the massive news.Therefore,effective news recommendation algorithms are urgently needed to solve this problem.After introducing the role and development process of news recommendation algorithms,firstly,the composition of each module of news recommendation algorithms is introduced;secondly,ac-cording to the characteristics of the algorithm,it is divided into traditional news recommendation algorithms and news recommenda-tion algorithms based on deep learning.For news recommendation algorithms based on deep learning,they are further divided into news recommendation algorithms with and without additional information.Afterwards,news recommendation algorithms with addi-tional information are further divided into news recommendation algorithms based on time,location,social,and conversation,and introduced separately.Then,the dataset of news recommendation algorithms and various evaluation indicators were summarized.Finally,the possible future development and research directions in the field of news recommendation were discussed.
news recommendationrecommendation algorithmdeep learningevaluation index
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