Dimensionalitycurse and dimensionalityreduction are two issues that have retained highinterest for data mining, machine learning, multimedia indexing, and clustering. We present a...
Caetano Traina Jr., Agma J. M. Traina, Leejay Wu, ...
Dimensionality reduction is a commonly used step in many algorithms for visualization, classification, clustering and modeling. Most dimensionality reduction algorithms find a low...
We propose an aspect-model-based reference speaker weighting. The main idea of the approach is that the adapted model is a linear combination of a set of reference speakers like r...
: The rapid progresses in human genome project and biotechnologies result in the sheer volume of datasets associated with in-depth scientific knowledge. Metabolomics is defined as ...
The widespread use of RDF-based information necessitates efficient information retrieval techniques in wide-area networks. In this paper, we present Dynamic Semantic Space, a sche...