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 …

The automatic disambiguation of word senses hasbeen an interest and concern since the
earliest days of computer treatment of language in the 1950s. Sense disambiguation is an" …

This article presents a measure of semantic similarity in an IS-A taxonomy based on the
notion of shared information content. Experimental evaluation against a benchmark set of …

A comprehensive theory-based approach to the treatment of text meaning in natural
language processing applications. In Ontological Semantics, Sergei Nirenburg and Victor …

Parallel texts (bitexts) have properties that distinguish them from other kinds of parallel data.
First, most words translate to only one other word. Second, bitext correspondence is typically …

This paper describes automatic construction a freely-available wordnet for French (WOLF)
based on Princeton WordNet (PWN) by using various multilingual resources. Polysemous …

Resnik and Yarowsky (1997) made a set of observations about the state-of-the-art in
automatic word sense disambiguation and, motivated by those observations, offered several …

Words have different meanings (ie, senses) depending on the context. Disambiguating the
correct sense is important and a challenging task for natural language processing. An …

We demonstrate the effectiveness of multilingual learning for unsupervised part-of-speech
tagging. The key hypothesis of multilingual learning is that by combining cues from multiple …

Int. Cl. G06F 7/30(2006.01) Systems and methods for word sense disambiguation,(52) US
Cl................................................ 707/5: 707/3 including discerning one or more senses or …