The major disadvantage of hierarchical clustering in fMRI data analysis is that an appropriate clustering threshold needs to be specified. Upon grouping data into a hierarchical tree, clusters are identified either by specifying their number or by choosing an appropriate inconsistency coefficient. Since the number of clusters present in the data is not known beforehand, even a slight variation ...

The molecular vibration-activity relationship in the receptor-ligand interaction of adenosine receptors was investigated by structure similarity, molecular vibration, and hierarchical clustering in a dataset of 46 ligands of adenosine receptors. The resulting dendrogram was compared with those of another kind of fingerprint or descriptor. The dendrogram result produced by corralled intensity of...

Dendrograms used in data analysis are ultrametric spaces, hence objects of nonarchimedean geometry. It is known that there exist p-adic representations of dendrograms. Completed by a point at infinity, they can be viewed as subtrees of the Bruhat-Tits tree associated to the p-adic projective line. The implications are that certain moduli spaces known in algebraic geometry are in fact p-adic par...

To make it easier to understand the machine translation evaluation results, a curve is utilized to stand for the performance of a machine translation system. The position of the curve in the graph depicts the quality of the system. The upper left curve stands for higher translation quality. System clustering is made and its dendrogram illustrates the quality difference between systems. These tw...

The paper proposes a new strategy called HAMIS to improve NPS (Net Promoter Score) of certain companies involved in heavy equipment repair in the US and Canada we call them clients. HAMIS is based on the semantic dendrogram built by using agglomerative clustering strategy and semantic distance between clients. More similar is the knowledge extracted from two clients, more close these clients se...

We demonstrate the utility of dendrograms at representing the essential features of the hierarchical structure of the isosurfaces for molecular line data cubes. The dendrogram of a data cube is an abstraction of the changing topology of the isosurfaces as a function of contour level. The ability to track hierarchical structure over a range of scales makes this analysis philosophically different...

A conceptual framework for cluster analysis from the viewpoint of p-adic geometry is introduced by describing the space of all dendrograms for n datapoints and relating it to the moduli space of p-adic Riemannian spheres with punctures using a method recently applied by Murtagh (2004b). This method embeds a dendrogram as a subtree into the Bruhat-Tits tree associated to the p-adic numbers, and ...

We consider the wavelet transform of a finite, rooted, node-ranked, p-way tree, focusing on the case of binary (p = 2) trees. We study a Haar wavelet transform on this tree. Wavelet transforms allow for multiresolution analysis through translation and dilation of a wavelet function. We explore how this works in our tree context.

Hierarchies are effective data models for organizing textual collections, particularly for automatic document classification into categories and subcategories. However, the majority of existing methods on hierarchical classification require human-labeled document set. Moreover, humans have good insight to manage the categories of higher levels of the hierarchy, i.e., more general categories, wh...