Forecasting future events based on historic data is useful in many domains like system management, adaptive query processing, environmental monitoring, and financial planning. We...
We propose a novel, high-level model of human learning and cognition, based on association forming. The model configures any input data stream featuring a high incidence of repeti...
Abstract-- Simultaneously clustering columns and rows (coclustering) of large data matrix is an important problem with wide applications, such as document mining, microarray analys...
Clustering is an essential data mining task with various types of applications. Traditional clustering algorithms are based on a vector space model representation. A relational dat...
We address aggregate queries over GIS data and moving object data, where non-spatial information is stored in a data warehouse. We propose a formal data model and query language t...