BACKGROUND There are several humanly defined ontologies relevant to Medline. However, Medline is a fast growing collection of biomedical documents which creates difficulties in updating and expanding these humanly defined ontologies. Automatically identifying meaningful categories of entities in a large text corpus is useful for information extraction, construction of machine learning features,...

Finding an appropriate structure that represents the information contained in texts is not a trivial task. There are different structures for modeling the knowledge, such as: ontologies, taxonomies, thesaurus, and semantic networks. Ontologies are especially useful because they support the exchange and sharing of information. An important task in ontology learning is to obtain a set of represen...

Theories of lexical access in language use of a productive nature such as speaking, writing, and verbal thinking differ in whether they assume that words are retrieved from memory in a conceptually decomposed or nondecomposed manner. Decomposition has been the received view for centuries, while nondecomposition is mostly not taken very seriously—undeservedly so, as 1 demonstrate in this paper. ...

This paper addresses the issue of how semantic information can be automatically assigned to compound terms, i.e. both a definition and a set of semantic relations. This is particularly crucial when elaborating multilingual databases and when developing cross-language information retrieval systems. The paper shows how morphosemantics can contribute in the constitution of multilingual lexical net...

Some approaches to automatic terminology extraction from corpora imply the use of existing semantic resources for guiding the detection of terms. Most of these systems exploit specialised resources, like UMLS in the medical domain, while a few try to take profit from general-purpose semantic resources, like EuroWordNet (EWN). As the term extraction task is clearly domain depending, in the case ...

Knowledge-poor corpus-based approaches to natural language processing are attractive in that they do not incur the difficulties associated with complex knowledge bases and real-world inferences. However, these kinds of language processing techniques in isolation often do not suffice for a particular task; for this reason we are interested in finding ways to combine various techniques and improv...

Formal concept analysis as a methodology of data analysis and knowledge representation has potential to be applied to a variety of linguistic problems. First, linguistic applications often involve the identification and analysis of features, such as phonemes or syntactical or grammatical markers. Formal concept analysis can be used to record and analyze such features. The line diagrams of conce...

A variety of methods exist for extracting terms and relations between terms from a corpus, each of them having strengths and weaknesses. Rather than just using the joint results, we apply different extraction methods in a way that the results of one method are input to another. This gives us the leverage to find terms and relations that otherwise would not be found. Our goal is to create a sema...

Ontologies as well as classification systems and thesauri consist of concepts and the paradigmatic semantic relations between them. Paradigmatic relations are document-independent relations used to model a domain of interest; in contrast to syntagmatic relations, which are merely based on the co-occurrence of concepts within single documents (Stock & Stock, 2008, pp. 68-70). Paradigmatic relati...

A method of sense resolution is proposed that is based on WordNet, an on-line lexical database that incorporates semantic relations (synonymy, antonymy, hyponymy, meronymy, causal and troponymic entailment) as labeled pointers between word senses. With WordNet, it is easy to retrieve sets of semantically rehted words, a facility that will be used for sense resolution during text processing, as ...