The invention discloses an address information feature extraction method based on a deep neural network model. According to the method, tasks such as text feature extraction, address standardization construction and semantic space fusion are converted into quantifiable deep neural network model construction and training optimization problems by utilizing a deep neural network architecture. Characters in an address are used as basic input units, a language model is designed to express the characters in a vectorization mode, and then the key technology of place name and address standardized construction is achieved through a neural network target task. Meanwhile, considering place name address space expression characteristics, proposing an address semantic-space characteristic fusion scheme,designing a weighted clustering method and a characteristic fusion model, and extracting a fusion vector fused with semantic characteristics and space characteristics from an address text of a natural language. The feature content extraction of the address information can be realized. The structure has high expansibility. The solution thinking of address information tasks can be unified. The method is of great significance to urban construction.