According to the feature of great computation for Text Clustering, This paper presents a new Text Clustering method which takes the advantages of concept lattice and Newman Fast algorithm. The algorithm firstly expresses the text as Feature word set and the technology extracting feature vector by statistical method. Secondly, using the TFIDF weight formula computes the weight of words and making discrete in the words weight .Thirdly, using the form background expresses the keywords, using similarity formula Calculates the size of formal concept similarity . Fourth, building Newman network, clustering the text of cluster by the Newman network Algorithm rule. Last but not least, the experiment shows the validity of this method. It is not only take the right sort results, but Greatly reduces the complexity of the algorithm, Newman Fast algorithm complexity only is .