Text Clustering Based on the User Search Intention

This paper presents a novel algorithm of Text Clustering. With the popularity of the Internet, text information on the web shows explosive growth trend. Text Clustering technology as a method of unsupervised machine learning, which does not need the training process and pre-manual tagging, so Text Clustering is an effective way for dealing with massive text messages. The traditional Text Clustering is based on the content of the article, and they think that the articles which belong to the same class have the greater similarity. In this paper, we extracted label word from the summary information returned by search engine. Then did hierarchical clustering based on the text feature of the label word. Experiment shows that the algorithm is feasible.