A news-topic recommender system based on keywords extraction

In recent years, internet news has become one of the most important channels for information acquisition, as more and more people read news through internet connected computers, tablets, and smart phones, etc. Owing to the constantly reproduced news, the number of online media increases dramatically and the volume of news also expands rapidly. Consequently, obtaining primary information from the internet is of great interest. This paper presents a news-topic recommender system based on keywords extraction. It is shown that the proposed system is very effective in acquiring specific topics within any specific period of time.

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