Knowledge Discovery in time series usually requires symbolic time series. Many discretization methods that convert numeric time series to symbolic time series ignore the temporal ...
We introduce a new EM framework in which it is possible not only to optimize the model parameters but also the number of model components. A key feature of our approach is that we...
This paper investigates the use of supervised clustering in order to create sets of categories for classi cation of documents. We use information from a pre-existing taxonomy in o...
Multimedia Data Mining requires the ability to automatically analyze and understand the content. The Community of Multimedia Agents project (COMMA) is devoted to creating an open ...
The rapid growth of the world wide web had made the problem of topic speci c resource discovery an important one in recent years. In this problem, it is desired to nd web pages wh...