一般資訊檢索的研究著重於檢索模型的建構、查詢的回饋機制、檢索行為的探討、檢索系統的執行效能。 本文則把研究的重心回歸資訊或文件本身，希望對資訊的內容有一個初步的瞭解。 本文根據三個因素：1)詞彙的重複，2)詞彙的重要性，3)共容語意，提出一個基於真實語料的文件內容分析的模型。這樣的模可型重於文章中名詞╱動詞與名詞╱名詞之間的配對關係。 本文也說明如何使用文件分析模型進行文件切分與文件主題辦識的研究，同時討論相關實驗的結果。

　　　　　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 theis paper. It focuses on association norms of noun-noun relations and noun-verb relations defined on discourse level and sentencelevel, 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.