By analyzing the characteristics and disadvantages of the existing keywords extraction algorithms based on complex network, a new keywords extraction algorithm is proposed by using of weighted complex network. First of all, a weighted complex network model is constructed according to the relationship between the feature words of text. Secondly, the weighted clustering coefficient and betweeness are introduced to calculate the node's multi-feature value. Finally, the keywords are extracted by the multi-feature value. The experiment results show that the keywords extracted by this algorithm have great contribution to the text subject, and the accuracy of keywords extraction is better than the existing algorithms.