In this paper we describe the design and implementation of a C++ based Common Component Architecture (CCA) framework, XCAT-C++. It can efficiently marshal and unmarshal large data...
Madhusudhan Govindaraju, Michael R. Head, Kenneth ...
Identifying the patterns of large data sets is a key requirement in data mining. A powerful technique for this purpose is the principal component analysis (PCA). PCA-based clusteri...
Given Boolean data sets which record properties of objects, Formal Concept Analysis is a well-known approach for knowledge discovery. Recent application domains, e.g., for very lar...
The paper elaborates on the previous research on the analysis of temporal and spatio-temporal data done in statistical graphics and geo-visualization. We focus on the exploration ...
Abstract— Support vector machines are very accurate classifiers and have been widely used in many applications. However, the training and to a lesser extent prediction time of s...
Tong Luo, Lawrence O. Hall, Dmitry B. Goldgof, And...
Abstract. In the literature of data mining and statistics, numerous interestingness measures have been proposed to disclose succinct object relationships of association patterns. H...
Microaggregation is a technique used to protect privacy in databases and location-based services. We propose a new hybrid technique for multivariate microaggregation. Our techniqu...
— Recently several algorithms for clustering large data sets or streaming data sets have been proposed. Most of them address the crisp case of clustering, which cannot be easily ...
Although a huge amount of remote sensing data has been provided by Earth observation satellites, few data manipulation techniques and information extraction in large data sets hav...
Thales Sehn Korting, Leila Maria Garcia Fonseca, M...
Networked embedded acoustic sensors and imagers allow scientists to observe biological and environmental phenomena at high sampling rates and multiple scales. Such sampling can cr...
Michael Allen, Eric Graham, Shaun Ahmadian, Tetsun...