We describe a project undertaken by an interdisciplinary team combining researchers in
sleep psychology and in Natural Language Processing/Machine Learning. The goal is …

Abstract Word Sense Induction (WSI) is the task of identifying the different senses (uses) of a
target word in a given text. Traditional graph-based approaches create and then cluster a …

Sharing personal information and documents is pervasive in Web 2.0 environments, which
creates the need for properly controlling shared data. Most existing authorization and policy …

Ambiguous person names are a problem in many forms of written text, including that which
is found on the Web. In this paper we explore the use of unsupervised clustering techniques …

The Duluth systems that participated in task 11 of SemEval–2013 carried out word sense
induction (WSI) in order to cluster Web search results. They relied on an approach that …

This paper describes three University of Minnesota, Duluth systems that participated in the
I2B2 NLP smoker–status challenge. The task was to identify if a patient was a smoker based …

In this article, we present a novel statistical representation method for knowledge extraction
from a corpus containing short texts. Then we introduce the contrast parameter which could …

Unsupervised word sense discrimination relies on the idea that words that occur in similar
contexts will have similar meanings. These techniques cluster multiple contexts in which an …

A comunicação multilíngue é uma tarefa cada vez mais imperativa no cenário atual de
grande disseminação de informações em diversas línguas. Nesse contexto, são de grande …

We describe the application of unsupervised clustering methodologies to the problem of
discriminating among ambiguous names found in short passages of text that appear on Web …