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News happens all the time and many people have developed the habits of reading news. Among numerous news media, network media gets preference for its convenience and celerity. However, too much net-news results in information overload. So it is crucial to develop personalized news recommendation to help users pick up interesting news rapidly. With the growing of big news data and development of mobile internet, there are new chances and challenges in the domain of personalized news recommendation. Firstly, the challenges of personalized news recommendation are introduced. Secondly, an architecture of personalized news recommendation is proposed, which includes news profile, user profile, recommendation engine and user interface. Then based on this architecture, research development of each component is set forth. Thirdly, the methods of existing system of personalized news recommendation according with the architecture are displayed. Lastly, the datasets, evaluation methods, metrics and the possible research directions in the future are concluded.