This paper presents Domain Relevance Estimation (DRE), a fully unsupervised text categorization technique based on the statistical estimation of the relevance of a text with respe...
This paper presents a new method for Word Sense Disambiguation based on the WordNet Domains lexical resource [4]. The underlaying working hypothesis is tha...
Background: Word sense disambiguation (WSD) algorithms attempt to select the proper sense of ambiguous terms in text. Resources like the UMLS provide a reference thesaurus to be u...
Instances of a word drawn from different domains may have different sense priors (the proportions of the different senses of a word). This in turn affects the accuracy of word sen...
We develop latent Dirichlet allocation with WORDNET (LDAWN), an unsupervised probabilistic topic model that includes word sense as a hidden variable. We develop a probabilistic po...