This paper introduces an innovative approach for detecting a suboptimal partition starting from the dendrogram produced by a hierarchical clustering techinique. The approach exploits permutation tests and it can be used regardless of the agglomeration method and distance measure used in the classification process because it relies on the same criteria used for producing it. Moreover, the propos...

This paper describes the systems developed by the Center for Robust Speech Systems (CRSS), Univ. of Texas Dallas, for the National Institute of Standards and Technology (NIST) iVector challenge. Since the emphasis of this challenge is on utilizing unlabeled development data, our system development focuses on: 1) unsupervised clustering methods to estimate development data labels; 2) build effic...

In this paper a clustering algorithm for documents is proposed that adapts a sampling-based pruning strategy to simplify hierarchical clustering. The algorithm can be applied to any text documents data set whose entries can be embedded in a high dimensional Euclidean space in which every document is a vector of real numbers. This paper presents the results of an experimental study of the propos...

Text summarization system can save the time for user when reading large number of documents. The summary of text summarization system usually composed of meaningful sentence which represent content of text. The relations between keyword usually come from their cooccurrences in document. This study using hierarchical clustering method cluster sentences and apply concept formal analysis to find o...

Clustering is an important data mining technique. There are many algorithms that cluster either numeric or categorical data. However few algorithms cluster mixed type datasets with both numerical and categorical attributes. In this paper, we propose a similarity measure between two clusters that enables hierarchical clustering of data with numerical and categorical attributes. This similarity m...

Understanding the maintenance of high tropical tree species diversity requires disentangling the effects of habitat vs. geographic distance. Using floristic, topographic, and soil nutrient data from 105 0.6-ha plots in mixed dipterocarp forest throughout Sarawak, Malaysian Borneo, we explore the degree to which floristic patterns are habitat-driven from local to landscape scales. We assess how ...

Using cosmological N-body simulations of critical (SCDM) and open (Ω=0.3, OCDM) cold dark matter models we have identified dark matter halos which are associated with the progenitors of present day bright early–type galaxies. By following their merging history, we show how early–type galaxies that formed within massive halos at redshift ' 3 are now preferentially residing in clusters and groups...

This paper presents various Hierarchical Clustered based routing protocols of the WSN in the literature and explains its benefits. These protocols are designed to prolong the lifetime of network by minimizing the energy consumption of the sensor nodes. We scrutinize and compare several aspects and characteristics of few widely explored hierarchical clustering protocols, and its processes in wir...

A central problem in analysis of gene expression data is clustering of genes with similar expression profiles. In this paper, I describe an hierarchical clustering procedure that is based on simple probabilistic model. This procedure clusters genes with respect to a target classification of conditions, so that genes that are expressed similarly in each group of conditions are clustered together.

A problem with the modelling of clusters as d dimensional centroids is that centroids cannot relay much information about cluster shape i.e. elongated, circular, irregular etc... The Agglomerative-Partitional Clustering (APC) methodology introduced here attempts to remedy this situation by joining together centroids coexisting within regions of relatively high density with line segments. Interc...