An important step to understand text is to build the discourse structure through cohesion and coherence. However, to build the discourse structure in turn depends on the full understanding of texts, so that many efforts on this line are not automatic and not successful. A corpus-based model based on 1) repetition of words, 2) importance of words, and 3) collocational semantics for texts is proposed in this paper. It focuses on association norms of noun-noun relations and noun-verb relations defined on discourse level and sentence level, respectively. According to this model, a text partition algorithm is proposed to determine the boundaries of discourse structures and a topic identification algorithm is also presented. The results of a series of experiments show that the proposed model is promising.