Study of automatic annotation based on news tags

Abstract

In recent years, with the rapid development of Internet technology and digital media technology, information dissemination has entered the era of media integration. Meanwhile, the support of big data technologies promotes the deep integration of traditional media and new media. The media industry is undergoing profound changes. The management and dissemination of news are not only faced with opportunities, but also faced many challenges. How to push the news and customized content to users timely and dynamically, so as to save the searching time, becomes a hot area of current research. A news correlation approach based on tags is proposed to provide users with a personalized news service. The system takes advantage of the network information crawling, web-based text mining and personalized recommendations technologies to realize automated extraction of news tag. The innovation of this mode is that the tag contains both categories and keywords. It contains a classification subject to the advantage of clustering, but also includes the theme of keywords intuitive expression. In other words, it matches the user's search habits. Thus, this system can improve the ability to retrieve and manage the news.