Abstract: As a simple, effective and non-parametric classification algorithm, kNN method has been widely used in text classification. In order to improve the efficiency of classification,We proposed a fast kNN text classification algorithm based on area division. We divided the training set into several parts based on their area distribution, and then according to the relative positions between test patterns and those parts, easily found out k nearest neighbours of the test patterns in the training set. hhis will sharply cut down the amount of calculation of kNN algorithm Mathematical reasoning and the experimental results both show that this algorithm significantly improves the efficiency of classification while keeping the same accuracy rate of kNN classifier algorithm.

Key words: Text classification,K-nearest neighbor algorithm,Clustering,K-means algorithm