Hierarchical clustering algorithms can be agglomerative or divisive, depending on how partitions are formed. Such algorithms have advantages mainly related to the desired level of granularity the partition should have. The work described in this paper approaches two hierarchical algorithms, one agglomerative (and three of its variants) and the other divisive, focusing on their performance in un...

We present two results which arise from a model-based approach to hierarchical agglomerative clustering. First, we show formally that the common heuristic agglomerative clustering algorithms – Ward’s method, single-link, complete-link, and a variant of group-average – are each equivalent to a hierarchical model-based method. This interpretation gives a theoretical explanation of the empirical b...

This work investigated three techniques to automatically cluster a collection of documents: Word-Intersection with GQF, Word-Intersection with hierarchical agglomerative clustering, and TreeClustering. The Word-Intersection algorithms have been previously described in the literature while the TreeClustering technique is novel to this work. The TreeCluster algorithm idea comes from rule inductio...

Agglomerative hierarchical speaker clustering (AHSC) has been widely used for classifying speech data by speaker characteristics. Its bottom-up, one-way structure of merging the closest cluster pair at every recursion step, however, makes it difficult to recover from incorrect merging. Hence, making AHSC robust to incorrect merging is an important issue. In this paper we address this problem in...

Asymmetric cluster analysis is one of the most useful methods together with asymmetric multidimensional scaling (MDS) to analyze asymmetric (dis)similarity data. In both methods, visualization of the result of the analysis plays an important role in the analysis. Some methods for visualizing the result of the asymmetric clustering and MDS have been proposed (Saito and Yadohisa, Data Analysis of...

Performing clustering analysis on a large amount of historical trajectory data can obtain information such as frequent flight patterns aircraft and air traffic flow distribution, which provide reference for the revision standard procedures optimization division airspace sectors. At present, most uses single algorithm. When other processing remains unchanged, it is difficult to improve effect by...

Cluster ensembles organically integrate individual component methods which may utilise different parameter settings and features, and which may themselves be generated on the basis of different representations and learning mechanisms. Such a technique offers an effective means for aggregating multiple clustering results in order to improve the overall clustering accuracy and robustness. Many to...

INTRODUCTION Although people with knee and hip osteoarthritis (OA) seek treatment because of pain, many of these individuals have commonly co-occurring symptoms (for example, fatigue, sleep problems, mood disorders). The purpose of this study was to characterize adults with OA by identifying subgroups with the above comorbid symptoms along with illness burden (a composite measure of somatic sym...