The validity of semantic inferences depends on the contexts in which they are applied. We propose a generic framework for handling contextual considerations within applied inferen...
Idan Szpektor, Ido Dagan, Roy Bar-Haim, Jacob Gold...
The development of structure-learning algorithms for gene regulatory networks depends heavily on the availability of synthetic data sets that contain both the original network and ...
Koenraad Van Leemput, Tim Van den Bulcke, Thomas D...
The usefulness of the results produced by data mining methods can be critically impaired by several factors such as (1) low quality of data, including errors due to contamination, ...
Fang Chu, Yizhou Wang, Carlo Zaniolo, Douglas Stot...
This paper addresses the following question: how should we update our beliefs after observing some incomplete data, in order to make credible predictions about new, and possibly i...
In this paper, we investigate how to scale hierarchical clustering methods (such as OPTICS) to extremely large databases by utilizing data compression methods (such as BIRCH or ra...
Markus M. Breunig, Hans-Peter Kriegel, Peer Kr&oum...