关键词: 短信聚类, Isomap算法, 语义空间

Abstract: The calculating way proposed in this paper is to calculate the likeness degree of Chinese message and a message is gottern which embedded in the semantic space by using the Isomap method.This paper analyzes the messages according to the different clustering types in low-dimensional embedding.This algorithm has overcome difficulties in analyzing messages of traditional clustering types on different layers，and it has also overcome weakness of word frequency statistics which can not gather the similar meaning messages together.Experimental result indicates the algorithm is effective.

Key words: short messages clustering, Isomap algorithm, semantic space