We are working on a project aimed at building next generation analyst support tools that focus analysts’ attention on the most critical and novel information found within the da...
Eficient and efiective discovery of resource and knowledge from the Internet has become an imminent research issue, especially with the advent of the Information Super-Highway. A ...
Knowledge discovery systemsfor databasesareemployedto provide valuable insights into characteristics and relationshipsthat may exist in the data,but are unknown to the user. This ...
James S. Ribeiro, Kenneth A. Kaufman, Larry Kersch...
A considerable amount of e-learning content is being delivered via virtual or managed learning environments. These platforms keep track of learners' activities including cont...
We review some approaches to qualitative uncertainty and propose a new one based on the idea of Absolute Order of Magnitude. We show that our ideas can be useful for Knowledge Disc...
Numerous measures are used for performance evaluation in machine learning. In predictive knowledge discovery, the most frequently used measure is classification accuracy. With new...
Both, the number and the size of spatial databases, such as geographic or medical databases, are rapidly growing because of the large amount of data obtained from satellite images,...
The results of knowledge discovery in databases could vary depending on the data mining method. There are several ways to select the most appropriate data mining method dynamicall...
Seppo Puuronen, Vagan Y. Terziyan, Alexander Logvi...
Knowledge discovery, that is, to analyze a given massive data set and derive or discover some knowledge from it, has been becoming a quite important subject in several fields incl...
The alternating decision tree brings comprehensibility to the performance enhancing capabilities of boosting. A single interpretable tree is induced wherein knowledge is distribute...
Bernhard Pfahringer, Geoffrey Holmes, Richard Kirk...