The Web is a continuously evolving environment, since its content is updated on a regular basis. As a result, the traditional usagebased approach to generate recommendations that ...
Existing association rule mining algorithms suffer from many problems when mining massive transactional datasets. Some of these major problems are: (1) the repetitive I/O disk sca...
: In this paper we propose an application of data mining methods in the prediction of the availability and performance of Internet paths. We deploy a general decision-making method...
Bayesian text classifiers face a common issue which is referred to as data sparsity problem, especially when the size of training data is very small. The frequently used Laplacian...
In this paper, we present a general framework to discover spatial associations and spatio-temporal episodes for scientific datasets. In contrast to previous work in this area, fea...