Word sense disambiguation (WSD) is the ability to identify the meaning of words in context
in a computational manner. WSD is considered an AI-complete problem, that is, a task …

Since its inception in the mid-1980s, the General Practice Research Database (GPRD) has
undergone many changes but remains the largest validated and most utilised primary care …

Artificial Intelligence federates numerous scientific fields in the aim of develo** machines
able to assist human operators performing complex treatments---most of which demand high …

We examine tone dispersion, or the degree to which tone words are spread evenly within a
narrative, to evaluate whether narrative structure provides insight into managers' voluntary …

Abstract Word Sense Disambiguation (WSD) systems automatically choose the intended
meaning of a word in context. In this article we present a WSD algorithm based on random …

The knowledge acquisition bottleneck strongly affects the creation of multilingual sense-
annotated data, hence limiting the power of supervised systems when applied to multilingual …

Abstract Word Sense Disambiguation (WSD) and Word Sense Induction (WSI) are two
fundamental tasks in Natural Language Processing (NLP), ie, those of, respectively …

This article presents a new model for word sense disambiguation formulated in terms of
evolutionary game theory, where each word to be disambiguated is represented as a node …

System-related engineering tasks are often conducted using process models. In this context,
it is essential that these models do not contain structural or terminological inconsistencies …

Contextual embeddings are proved to be overwhelmingly effective to the task of Word Sense
Disambiguation (WSD) compared with other sense representation techniques. However …