Abstract:

In order to  get high qualitative clustering results, the noun phrases was selected as candidate cluster labels and generates basic clusters based on the distribution of candidate cluster labels. And then multi-level clustering was proceeded on basic clusters by using one pass clustering algorithm with linear time complexity. The comparative experiment was carried with our method, NEC algorithm, STC algorithm and Lingo  algorithm, and the results showed that our method could get more informative, readable cluster labels and more effective than other three methods.

Key words: information retrieval; search results clustering; text clustering; multi-level clustering