Nowadays people spend lots of time on browsing news on the Internet. News comment as one of the most common things that people find on the website, is earning more attention than before. News comments have significant impacts on people's decision and behavior as news itself. People find that they are always overwhelmed by massive comments and valuable comments are drowned in large amounts of uninteresting comments. This paper presents a multi-dimensional classification system and the personalized recommendation system of news comments, which aims to provide comments classification and personalized recommendation services. With this system, users will get a better users experience and get a comprehensive view of the news and comments with cheaper time cost.