In recent years, many traditional news websites developed corresponding recommendation systems to cater to readers’ interests and news recommendation systems are widely applied in traditional PCs and mobile devices. News recommendation system has become a critical research hotspot in the field of recommendation system. As News contains more text information, it is more helpful to improve the recommendation effect to obtain the content related to news features (location, time, events) from the news. This survey summarizes news features-based recommendation methods including location-based news recommendation methods, time-based news recommendation methods, events-based news recommendation methods. It helps researchers to know the application of news features in news recommendation methods. Also, this suvery summarizes the challenges faced by the news recommendation system and the future research direction.
CITATION STYLE
Qin, J., & Lu, P. (2020). Application of News Features in News Recommendation Methods: A Survey. In Communications in Computer and Information Science (Vol. 1258 CCIS, pp. 113–125). Springer. https://doi.org/10.1007/978-981-15-7984-4_9
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