基于Ant-Tree算法的短文本聚类研究

Short-text document clustering is considered more difficult than general document due to the low frequencies of the terms. Its ruesult is not good or acceptable by the normal clustering algorithm like K-means.However, some recent works, new bioinspired clustering algorithms and novel uses of Internal Clustering Validity Measures have been presented to deal with this difficult problem. In this paper, an improved Ant-Tree algorithm for the short-text clustering is proposed. The algorithm uses K-means algorithm to obtain an initial grouping, sort the them in decreasing order according to the Silhouette Coefficient. The ordering will be used by Ant-Tree's initial step. By this way, the performance of Ant-Tree will be improved. Experimental study shows that this method is more accurate efficient than other algorithms.