One solution to process and analysis of massive graphs is summarization. Generating a high quality summary is the main challenge of graph summarization. In the aims of generating a summary with a better quality for a given attributed graph, both structural and attribute similarities must be considered. There are two measures named density and entropy to evaluate the quality of structural and at...

Many heterogeneous sensors exhibit a strong correlation in both space and time that can be used to enhance the abnormal node detection problem wireless sensor network (WSN). Corruption these correlations has been shown effective detecting false data injection attacks. However, extracting such is considered challenging task WSNs. In this paper, we adopt new cross-correlation-based method extract...

Decision trees are, besides decision rules, one of the most popular forms of knowledge representation in Knowledge Discovery in Databases process (Fayyad, Piatetsky-Shapiro, Smyth & Uthurusamy, 1996) and implementations of the classical decision tree induction algorithms are included in the majority of data mining systems. A hierarchical structure of a tree-based classifier, where appropriate t...

We propose a model-based approach to identifying clusters of objects based on subsets of attributes, so that the attributes that distinguish a cluster from the rest of the population, called an attribute ensemble, may depend on the cluster being considered. The model is based on a Pólya urn cluster model, which is equivalent to a Dirichlet process mixture of multivariate normal distributions. T...

Multivariate volume visualization is important for many applications including petroleum exploration and medicine. State-of-the-art tools allow users to interactively explore volumes with multiple linked parameter-space views. However, interactions in the parameter space using trial-and-error may be unintuitive and time consuming. Furthermore, switching between different views may be distractin...