Short text classification is a key technology in network content security application.However

the sparse features and unbalanced data of the short text make the traditional text classification method incompetent for short text classification.This paper proposed a dynamic assembly classification method for short text classification.In this method

a treelike assembly classifier was constructed to support the classification

which reduced the impact of the sparse features and unbalanced data of the short texts.Further

a dynamic adjusting strategy was presented in the construction procedure

which adjusted the combinational structure of the classifier in an adaptive way.The experimental results show that

comparing with the traditional classifiers such as single classifier and ensemble classifier

the proposed assembly classifier gets better precision rate and recall rate.