Incomplete Clustering for Large Scale Short Texts
Chunyang Liu · Zhongwen xinxi xuebao · 2011
Clustering is an unsupervised classification of patterns(observations,data items,or feature vectors) into groups(clusters).So far,many clustering algorithms have been proposed.With the rapid development of internet,short texts such as query logs and Twitter messages play a more and more important role in our daily life.Most existing clustering methods are hard to be applied in dealing with this kind of information due to the huge scale of data.This paper reveals the long tail distribution of this kind of information,and proposes an incomplete clustering algorithm.The experimental results show that the proposed method can cluster the short texts effectively and efficiently.