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...

the present study investigated the effect of marginal glosses (both l1 and l2) on incidental vocabulary learning of efl learners. the subject pool consisted of 154 third-semester iranian students enrolled at azad university, central branch. after administering a proficiency test, 90 homogeneous students were assigned to two experimental groups (x1 & x2) and one control group. afterwards, a 50 -...

This paper proposes a machine learning approach to the task of assigning the international standard on classification of diseases ICD-9-CM codes to clinical records. By treating the task as a text categorisation problem, a classification system was built which explores a variety of features including negation, different strategies of measuring gloss overlaps between the content of clinical reco...

eValency Lexicon of Czech Verbs (VALLEX 2.0) is a collection of linguistically annotated data and documentation. It provides information on the valency structure of verbs in their particular meanings / senses, possible morphological forms of their complementations and additional syntactic information, accompanied with glosses and examples. e primary goal of the following text is to briefly de...

This paper studies the application of text similarity methods to disambiguate ambiguous links between WordNet nouns and Wikipedia categories. The methods range from word overlap between glosses, random projections, WordNetbased similarity, and a full-fledged textual entailment system. Both unsupervised and supervised combinations have been tried. The goldstandard with disambiguated links is pub...

This paper proposes a machine learning approach to the task of assigning the international standard on classification of diseases ICD-9-CM codes to clinical records. By treating the task as a text categorisation problem, a classification system was built which explores a variety of features including negation, different strategies of measuring gloss overlaps between the content of clinical reco...

A critical prerequisite for human-level cognitive systems is having a rich conceptual understanding of the world. We describe a system that learns conceptual knowledge by deep understanding of WordNet glosses. While WordNet is often criticized for having a too fine-grained approach to word senses, the set of glosses do generally capture useful knowledge about the world and encode a substantial ...