Exploiting Feature Selection Algorithm on Group Events Data Based on News Data

As traditional media and new media such as Weibo and WeChat are increasingly used, Internet has become the main supporter of thoughts of groups or individuals, which plays a key role in guidance of our daily life and society development. This study aims to investigate/propose a note feature extraction algorithm of data processing in massive news data, extracting the key words in the news and clarifying the important ones. We try to propose a revised STF algorithm and have comparisons between efficiency of various algorithms. Experiments showed that the proposed algorithm is 4% higher on the classification accuracy than other algorithms.