针对聚类融合算法可能出现信息失真等问题,提出一种新的聚类融合算法.该算法兼顾聚类质量与成员多样性,采用一种新的相似性度量,并依据度量结果先对聚类成员进行剪辑操作,再分组、选择,最后根据每个聚类成员对于各类别的贡献设计了一种新的加权函数.与其他方法相比,该方法具有较好的稳定性和精确性. In order to solve the problem that information fusion may occur in clustering fusion algorithm, a new clustering fusion algorithm is proposed. This algorithm takes into account the clustering quality and membership diversity, adopts a new similarity measure, Finally, according to each cluster member’s contribution to each category, a new weighting function is designed.Compared with other methods, this method has better stability and accuracy.