In this paper we study the notion of entropy for a set of attributes of a table and propose a novel method to measure the dissimilarity of categorical data. Experiments show that our estimation method improves the accuracy if the popular unsupervised Self Organized Map (SOM), in comparison to Euclidean or Mahalanobis distance. The distance comparison is applied for clustering of multidimensiona...

Result rankings from context-aware information retrieval are inherently dynamic, as the same query can lead to significantly different outcomes in different contexts. For example, the search term Digital Camera will lead to different – albeit potentially overlapping – results in the contexts Customer Reviews and Shops, respectively. The comparison of such result rankings can provide useful insi...

A dissimilarity measure between adjacent pixels of an image is usually determined by the intensity values of these pixels and therefore does not depend on statistics computed over the whole image domain. In this paper, new dissimilarity measures exploiting image statistics are proposed. This is achieved by introducing the notion of dissimilarity function defined for every possible pair of inten...

Game consoles allow subjects to perform movements which are visually similar to the movements performed in 'real' world scenarios. Beyond entertainment, virtual reality devices are being used in several domains: sports performance; motor rehabilitation; training of risk professions. This article presents the Procrustes method to measure the degree of dissimilarity between movements performed in...

Several researchers have developed properties that ensure compatibility of a concept similarity or dissimilarity measure with the formal semantics of Description Logics. While these authors have highlighted the relevance of the triangle inequality, none of their proposed dissimilarity measures satisfy it. In this work we present several dissimilarity measures with this property: first, a simple...

BACKGROUND The comparison of samples, or beta diversity, is one of the essential problems in ecological studies. Next generation sequencing (NGS) technologies make it possible to obtain large amounts of metagenomic and metatranscriptomic short read sequences across many microbial communities. De novo assembly of the short reads can be especially challenging because the number of genomes and the...

Defining a good distance (dissimilarity) measure between patterns is of crucial importance in many classification and clustering algorithms. While a lot of work has been performed on continuous attributes, nominal attributes are more difficult to handle. A popular approach is to use the value difference metric (VDM) to define a real-valued distance measure on nominal values. However, VDM treats...

Classification of spectral data has raised a growing interest in may research areas. However, this type of data usually suffers from the curse of dimensionality. This causes most statistical methods and/or classifiers to not perform well. A recently proposed alternative which can help avoiding this problem is the Dissimilarity Representation, in which objects are represented by their dissimilar...

The problem of multiple object classification based on discordant and non-specific data is considered. A general methodology for solving this problem is suggested and a suboptimal single-scan algorithm, referred to as the the global nearest neighbour (GNN), is implemented. The exact global dissimilarity measure, which is minimised by the GNN algorithm, is derived within the framework of the bel...