Automated Multiple Hierarchical Classification of Web News of Unexpected Events

To accurately classify Web news of unexpected events,an automated multiple hierarchical classification method is proposed.Firstly,the classification of Web news of unexpected events is analyzed in brief and three classifiers are constructed.The first and the second classifier are accomplished by the rules,while the third one needs to be realized by machine learning.Much more attention then is paid to Vector Space Model and feature extraction in HTML text.At last,the experiments which include the subjects of H1N1 influenza,French air crash and Wenchuan earthquake are conducted and analyzed.The results show that the method introduced is better than traditional methods.