This paper proposes a named entity recognition method based on Attention-BiLSTM (attention-bidirectional long short-term memory) deep neural network. Using BiLSTM neural network to automatically learn the implicit features of text can solve the problem of long-distance dependence of traditional recognition methods. Attention mechanism is used to calculate the importance of text global features, obtain local features of text, and solve the traditional deep learning method can not fully extract the feature problem; adding Wikipedia knowledge in the pre-training process further improves the performance of the named entity recognition system. Experiments show that the proposed method achieves excellent recognition performance on the SIGHAN 2006 Bakeoff-3 evaluation data set.