Abstract. In this paper we elaborate on the challenges of learning manifolds that have many relevant clusters, and where the clusters can have widely varying statistics. We call su...
We demonstrate a system to automatically grab data from data intensive web sites. The system first infers a model that describes at the intensional level the web site as a collec...
Valter Crescenzi, Giansalvatore Mecca, Paolo Meria...
This paper presents a grammar-induction based approach to partitioning a Web page into several small pages while each small page fits not only spatially but also logically for mob...
Abstract. We present a formalization of lexicalized Recursive Transition Networks which we call Automaton-Based Generative Dependency Grammar (gdg). We show how to extract a gdg fr...
Abstract. In this paper we argue why it is necessary to associate linguistic information with ontologies and why more expressive models, beyond RDFS, OWL and SKOS, are needed to ca...
Paul Buitelaar, Philipp Cimiano, Peter Haase, Mich...