In previous studies, very few clustering ensemble algorithms considered the prior knowledge of the datasets.
在以前的研究中，很少有聚类融合算法考虑到加入这点。
Main works are as follows. A clustering ensemble algorithm based on prior knowledge and spectral analysis is proposed.
具体工作如下：提出了一种基于先验信息和谱分析的聚类融合算法。
In 2002, clustering ensemble was putted forward and got widely attention immediately, and became an increasingly hot topic.
2002年，聚类融合算法已经提出就得到广泛关注，成为聚类分析研究的新热点。
Taking the one-pass clustering algorithm as the basic algorithm for grouping data, the issue of clustering ensemble is investigated.
以一趟聚类算法作为划分数据的基本算法，讨论聚类融合问题。
After analyzing the traditional clustering algorithms, the paper presents a new clustering ensemble method based on K-means to cluster data.
本文在分析传统聚类算法的基础上，提出了一种聚类融合算法。
Clustering ensemble is inspired by multiple classifiers ensemble. As a novel research topic, clustering ensemble has been proved to improve the performance of traditional clustering algorithms.
受分类集成技术的启示，聚类集成作为当今的研究热点已被证明能有效地提高传统聚类算法的性能。
In this paper, cluster ensemble methods based on hierarchical clustering and clustering validity have been studied.
本文对基于层次聚类的簇集成方法及聚类的有效性进行了研究。
Recently, people begin to apply ensemble technology to the research of clustering methods and propose a number of cluster ensemble algorithms to improve the performance of these clustering algorithms.
为了提高聚类算法的性能，近年来人们开始将集成技术应用到聚类方法中的研究工作，并且提出了一些聚类集成算法。
Recently, people begin to apply ensemble technology to the research of clustering methods and propose a number of cluster ensemble algorithms to improve the performance of these clustering algorithms.
为了提高聚类算法的性能，近年来人们开始将集成技术应用到聚类方法中的研究工作，并且提出了一些聚类集成算法。
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