The topic tree-based topic structure model is proposed using five-tuple and probability theory of ontology. Vocabularies in the glossary are presented with leaf nodes of the topic tree. The results of simulation experiment on real news corpus eventually show that the topic similarity of sym-KL divergence could construct a topic tree more accurately and dig the potential semantic topic characteristics of time and space more deeply in the text stream compared with other flat topic structure models.