We present a novel approach to the automatic acquisition of taxonomies or concept
hierarchies from a text corpus. The approach is based on Formal Concept Analysis (FCA), a …

Wikipedia provides a semantic network for computing semantic relatedness in a more
structured fashion than a search engine and with more coverage than WordNet. We present …

We present a novel approach to learning taxonomic relations between terms by considering
multiple and heterogeneous sources of evidence. In order to derive an optimal combination …

Without the proliferation of formal semantic annotations, the Semantic Web is certainly
doomed to failure. In earlier work we presented a new paradigm to avoid this: the'Self …

Bridging reference resolution is an anaphora resolution task that is arguably more
challenging and less studied than entity coreference resolution. Given that significant …

The goal of giving a well-defined meaning to information is currently shared by endeavors
such as the Semantic Web as well as by current trends within Knowledge Management …

Ontology learning techniques serve the purpose of supporting an ontology engineer in the
task of creating and maintaining an ontology. In this chapter, we present a comprehensive …

We use machine learning techniques to find the best combination of local focus and lexical
distance features for identifying the anchor of mereological bridging references. We find that …

State-of-the-art research on automated learning of ontologies from text currently focuses on
inexpressive ontologies. The acquisition of complex axioms involving logical connectives …

The relation between ontologies and language is currently at the forefront of natural
language processing (NLP). Ontologies, as widely used models in semantic technologies …