Relation extraction is a difficult open research problem with important applications in several fields such as knowledge management, web mining, ontology building, intelligent sys...
Burst detection is the activity of finding abnormal aggregates in data streams. Such aggregates are based on sliding windows over data streams. In some applications, we want to mo...
In this paper, we consider the problem of combining link and content analysis for community detection from networked data, such as paper citation networks and Word Wide Web. Most ...
Sample selection bias is a common problem in many real world applications, where training data are obtained under realistic constraints that make them follow a different distribut...
We describe a method for computing closed sets with data-dependent constraints. Especially, we show how the method can be adapted to find frequent closed sets in a given data set...