After a concise introduction of conotation,functions and general processs of textual document clustering, this paper expotiates the basic mechanism of a kind of improved K-means clustering based on initial centroids selection through minimum-maximum principle, designs its algorithm, implements the clustering system, and conducts several experiments taking 300 academic articles and relative characteristic words for instances, which prove the good performance of the algorithm proposed.