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 …

One major deficiency of most semantic representation techniques is that they usually model
a word type as a single point in the semantic space, hence conflating all the meanings that …

The goal of this task is to allow for comparison across sense-induction and discrimination
systems, and also to compare these systems to other supervised and knowledgebased …

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

In this paper, we present a novel approach to Web search result clustering based on the
automatic discovery of word senses from raw text, a task referred to as Word Sense …

This paper explores the use of two graph algorithms for unsupervised induction and tagging
of nominal word senses based on corpora. Our main contribution is the optimization of the …

Word Sense Disambiguation (WSD), the process of automatically identifying the meaning of
a polysemous word in a sentence, is a fundamental task in Natural Language Processing …

This article describes the creation and application of the Turk Bootstrap Word Sense
Inventory for 397 frequent nouns, which is a publicly available resource for lexical …

We explore the contribution of distributional information for purely knowledge-based word
sense disambiguation. Specifically, we use a distributional thesaurus, computed from a …

This survey and analysis presents the functional components, performance, and maturity of
graph-based methods for natural language processing and natural language understanding …