User knowledge demand model establishing method based on Gaussian mixed model

The invention provides a method for establishing a user knowledge demand model by utilizing a Gaussian mixed model for the first time. Firstly, high-dimensional vectors of function words are generated by considering the semantic information of the function words based on a skip-gram model of knowledge base training word2vec, then the Gaussian mixed model is trained by utilizing selected knowledge corpus set, multiple Gaussian distributions are applied to describe the probability distributions of function word knowledge demands of a user, an EM method is applied to optimize parameters of the Gaussian mixed model; finally, the mapping relation between the words and entries is established, a knowledge entry demand model of the user is obtained, and knowledge entries, most possibly interested by the user, in a knowledge base are calculated on the basis and are pushed to the user. The established Gaussian mixed model can more closely fit the user knowledge demand model, and the knowledge push accuracy rate is impr