For hierarchical clustering, dendrograms provide convenient and powerful visualization. Although many visualization methods have been suggested for partitional clustering, their usefulness deteriorates quickly with increasing dimensionality of the data and/or they fail to represent structure between and within clusters simultaneously. In this paper we extend (dissimilarity) matrix shading with ...

Organizing data into hierarchies is natural for humans. However, there is little work in machine learning that explores human-machine mixed-initiative approaches to organizing data into hierarchical clusters. In this paper we consider mixed-initiative clustering of a user's email, in which the machine produces (initial and re-trained) hierarchical clusterings of email, and the user iteratively ...

We determine the basic categories and the hierarchy of rules used by humans in judging similarity and matching of color patterns. The categories are: (1) overall color; (2) directionality and orientation; (3) regularity and placement; (4) color purity; (5) complexity and heaviness. These categories form the pattern vocabulary which is governed by the grammar rules. Both the vocabulary and the g...

The taxonomy of N2-fixing bacteria belonging to the genus Bradyrhizobium is still poorly refined. This paper presents an application of a method aiming the identification of possible new clusters within a Brazilian collection of 119 Bradyrhizobium strains showing phenotypic characteristics of B. japonicum and B. elkanii. The stability has been studied as a function of the number of restriction ...

Hierarchical clustering of speakers by their pronunciation patterns could be a useful technique for the discovery of accents and the relationships between accents and sociological variables. However it is first necessary to ensure that the clustering is not influenced by the physical characteristics of the speakers. In this study a number of approaches to agglomerative hierarchical clustering o...

User groups identification is an important task in intelligent personalized information service. In this paper we proposed an intelligent information service model based on hierarchical clustering algorithms. There are two main works in this article: firstly, a vector models which can represent users' interests, preferences and emotional information is introduced. Secondly, a user groups cluste...

This article describes a novel way of representing large databases of shapes. We propose a hierarchical clustering of a set of Fourier-transformed contours. The clustering analysis is density-based and is performed using topographic maps. We have tested the approach on a database of extracted contours of marine animals, generated by Mokhtarian and co-workers. The resulting clusters group contou...

This study investigates a method for best member selection of a Limited area model Ensemble Prediction System (LEPS) with the goal to increase quantitative precipitation forecast. A case study that occurred between 22-24 May 2002 over Calabria, southern Italy, is discussed. Mediterranean storms often develop under upper level disturbances which are usually associated with high values of potenti...

clustering technique is one of the most important techniques of data mining and is the branch of multivariate statistical analysis and a method for grouping similar data in to same clusters. with the databases getting bigger, the researchers try to find efficient and effective clustering methods so that they can make fast and real decisions. thus, in this paper, we proposed an improved ant syst...