Abstract: We proposed a novel matching clustering algorithm by improving the method of clear rational number mean. First, we calculated the clear rational mean of each piece of data, then compared it with the matching item to get the clustering result, and solved the clustering problem of artificial annotation data. This method was tested and verified in the field of antifraudulent Web pages, and compared with the results of Knearest neighbor algorithm using the same name but different types of data sets. Experimental results show that the method is more effective than Knearest neighbor algorithm in the field of antifraudulent Web pages, and it also proves that the novel matching clustering algorithm is reasonable in clustering artificial annotation data.

Key words: clustering, matching, clear rational number mean, data mining