The label ranking problem consists of learning a model that maps instances to total orders over a finite set of predefined labels. This paper introduces new methods for label ra...
Abstract. We propose a novel active learning strategy based on the compression framework of [9] for label ranking functions which, given an input instance, predict a total order ov...
A weakly supervised method uses anonymized search queries to induce a ranking among class labels extracted from unstructured text for various instances. The accuracy of the extrac...
Mashups are situational applications that build data flows to link the contents of multiple Web sources. Often times, ranking the results of a mashup is handled in a materializethe...
Top-k processing in uncertain databases is semantically and computationally different from traditional top-k processing. The interplay between query scores and data uncertainty ma...
Mohamed A. Soliman, Ihab F. Ilyas, Kevin Chen-Chua...