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 …

Abstract Entity Linking (EL) and Word Sense Disambiguation (WSD) both address the lexical
ambiguity of language. But while the two tasks are pretty similar, they differ in a fundamental …

Since the last two decades, XML has gained momentum as the standard for web information
management and complex data representation. Also, collaboratively built semi-structured …

Word sense disambiguation (WSD), the task of identifying the intended meanings (senses)
of words in context, has been a long-standing research objective for natural language …

High-dimensional data arise naturally in many domains, and have regularly presented a
great challenge for traditional data mining techniques, both in terms of effectiveness and …

Web search result clustering aims to facilitate information search on the Web. Rather than
the results of a query being presented as a flat list, they are grouped on the basis of their …

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 …

We apply the integrated syntactic graph feature extraction methodology to the task of
automatic authorship detection. This graph-based representation allows integrating different …

Sequence labeling models for word sense disambiguation have proven highly effective
when the sense vocabulary is compressed based on the thesaurus hierarchy. In this paper …

Word sense induction aims to discover different senses of a word from a corpus by using
unsupervised learning approaches. Once a sense inventory is obtained for an ambiguous …