The invention relates to a method for analyzing implicit type discourse relation based on hierarchical depth semantics, and belongs to the technical field of application of natural language processing. The method comprises the following steps of firstly, combining marked and unmarked corpuses, expanding the corpus training scale, and solving the problem of under-learning due to undersize corpus training scale; then, according to a certain rule, initializing a depth semantic vector of each corpus training hierarchy, sorting word pairs favorable for classification according to information gain value, and using the word pairs as subsequent feature selection basis; finally, designing a scoring function, combining the multiple hierarchial depth semantic information of to-be-classified discourse relation theory element pairs, utilizing the parameters of a nerve network training model, fitting a type tag of the implicit type discourse relation, and finding the model for furthest optimizing the performance, so as to complete the analysis of the implicit type discourse relation. The method has the advantages that the false judging of the traditional method based on discrete features is overcome; the analysis accuracy of the type tag of the implicit type discourse relation is improved; a user can quickly and accurately obtain the analysis result of the implicit type discourse relation.