Abstract: The literature knowledge discoveries methods have become the breakthrough technologies to solve the difficult problem of massive information retrieval.But the current literature knowledge discovery methods are vector space methods based on word bag.This methods have congenital deficiency, i.e．semantic independence between vocabulary elements, so a large number of potential knowledge which exists between texts can't be discovered.Therefore, a new Chinese literature knowledge discovery method is put forward in this paper.The representation of the minimum knowledge unit and the semantic reasoning are based on subject predicate object (S,P,O) structure in this method.So the deficiency of traditional knowledge discovery method can be avoided, and a reasoning algorithm is proposed based on the structure to discover the potential knowledge between texts.The efficiency of discovering the potential of knowledge of our method is enhanced in contrast to the traditional methods, which is proved by the experiments in this paper.

Key words: Discovery in text,Semantic complementary reasoning,Knowledge element mining