A document taxonomy alignment method, relying on document glosses and utilizing a soft ontology expansion, enables us to devise some allnew hierarchical leaf nodes for the purpose of better aligning a plurality of document taxonomies.

How limitations are acknowledged and discussed has a profound impact on the extent research is evaluated accepted by its intended readers. However, little attention been drawn to presentation of in EAP literature. This study seeks remedy oversight exploring how this discursive practice mediated metadiscourse, rhetorically contextualized much these rhetorical investments differ between PhD disse...

This paper studies the enrichment of Spanish WordNet with synset glosses automatically obtained from the English WordNet glosses using a phrase-based Statistical Machine Translation system. We construct the English-Spanish translation system from a parallel corpus of proceedings of the European Parliament, and study how to adapt statistical models to the domain of dictionary definitions. We bui...

This paper presents a new method for Word Sense Disambiguation based on the WordNet Domains lexical resource [4]. The underlaying working hypothesis is that domain labels, such as ARCHITECTURE, SPORT and MEDICINE provide a natural way to establish semantic relations between word senses, that can be used during the disambiguation process. This resource has already been used on Word Sense Disambi...

The essential characteristic of a signed language corpus is that it has been annotated, and not, contrary to the practice of many signed language researchers, that it has been transcribed. Annotations are necessary for corpus-based investigations of signed or spoken languages. Multi-media annotation software can now be used to transform a recording into a machine-readable text without it first ...

OntoLearn is a system for automatic acquisition of specialized ontologies from domain corpora, based on a syntactic pattern matching technique for word sense disambiguation, called structural semantic interconnection (SSI). We use SSI to extract from corpora complex domain concepts and create a specialized version of WordNet. In order to facilitate the task of domain specialists who inspects an...

We review in detail here a polished version of the systems with which we participated in the Senseval2 competition English tasks (all words and lexical sample). It is based on a combination of selectional preference measured over a large corpus and hierarchical information taken from WordNet, as well as some additional heuristics. We use that information to expand sense glosses of the senses in...