Abox inference is an important part in OWL data management. When involving large scale of instance data, it can not be supported by existing inference engines. In this paper, we p...
Abstract. Ontologies are now used within an increasing number of realworld applications. So far, significant effort has been spend in building tools to support users in creating,...
This paper presents an efficient inference algorithm of conditional random fields (CRFs) for large-scale data. Our key idea is to decompose the output label state into an active s...
In this paper, we raise important issues on scalability and the required degree of supervision of existing Mahalanobis metric learning methods. Often rather tedious optimization p...
Background: The advent of RNA interference techniques enables the selective silencing of biologically interesting genes in an efficient way. In combination with DNA microarray tec...