In this paper we explore the application of a novel data collection scheme for multi-sensory information to the question of whether different sensory domains tend to show similar relations between objects (along with some unique variance). Our analyses—hierarchical clustering, MDS mapping, and other comparisons between sensory domains— support the existence of common representational schemes fo...

[Abstract] Quantization problem in digital control system have attracted more and more attention in these years. Normally, a quantized variable is regarded as a perturbed copy of the unquantized variable in the research of quantization effect, but this model has shown many obvious disadvantages in control system analysis and design process. In this paper, we give a new model for quantization ba...

A general parametric scheme of hierarchical clustering procedures with invariance under monotone transformations of similarity values and invariance under numeration of objects is described. This scheme consists of two steps: correction of given similarity values between objects and transitive closure of obtained valued relation. Some theoretical properties of considered scheme are studied. Dif...

The processing and management of XML data are popular research issues. However, operations based on the structure of XML data have not received strong attention. These operations involve, among others, the grouping of structurally similar XML documents. Such grouping results from the application of clustering methods with distances that estimate the similarity between tree structures. This pape...

I describe a semi-analytical model for the formation and evolution of galaxies in hierarchical clustering models, and its predictions for the properties of the galaxy population at high z. The predictions are found to agree well with the observed properties of the Lyman break galaxies found at z ∼ 3 by Steidel et al. . The models predict that the star formation rate per comoving volume should h...

Clustering is a discovering process of meaningful intbrmation by grouping similar data into compact clusters. Most of traditional clustering methods are in favor of small datasets and have difficulties handling very large datasets. They are not adequate clustering methods for partitioning huge datasets in data mining perspective. We propose a new clustering technique, HRC(hierarchical represent...

Population pyramid is a very popular presentation of the age-sex distribution of the human population of a particular region. The shape of the pyramid shows many demographic, social, and political characteristics of the time and the region. In the paper results of hierarchical clustering of the world countries based on population pyramids are presented. Special attention is given to the shapes ...

In this paper, we conduct a series of exploratory analyses on the user-recommended usages of music as generated by 1,042 reviewers who have posted to www.epinions.com. Using hierarchical clustering methods on data derived from the co-occurrence analyses of usage and genre, usage and artist, and usage and album, we are able to conclude that further investigation of user-recommended usage metadat...

Although clustering under constraints is a current research topic, a hierarchical setting, in which a hierarchy of clusters is the goal, is usually not considered. This paper tries to fill this gap by analyzing a scenario, where constraints are derived from a hierarchy that is partially known in advance. This scenario can be found, e.g., when structuring a collection of documents according to a...

This paper proposes a novel approach to group SPARQL query results according to their similarities. In order to compare results, the originality of our approach is to consider for each result the data constituting this result such as they are present and arranged in the queryed RDF dataset. We therefore do not limit ourselves to comparing the results between them, but we recontextualize them in...