The invention discloses a knowledge base completion method based on variational interference and a tensor neural network. Tensor decomposition thought and a Bayesian framework are introduced into the knowledge base completion method, and the prior knowledge of implicit variables is considered. The interaction between the implicit variables is discussed and nonlinear expression is performed through the neural network, and consideration of nondeterminacy is added. The accuracy of the knowledge base method is improved obviously, and compared with the existing technology, the knowledge base completion method has been greatly improved.