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» Automatic Word Sense Discrimination
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NAACL
2010
13 years 5 months ago
Taxonomy Learning Using Word Sense Induction
Taxonomies are an important resource for a variety of Natural Language Processing (NLP) applications. Despite this, the current stateof-the-art methods in taxonomy learning have d...
Ioannis P. Klapaftis, Suresh Manandhar
EMNLP
2004
13 years 9 months ago
Unsupervised WSD based on Automatically Retrieved Examples: The Importance of Bias
This paper explores the large-scale acquisition of sense-tagged examples for Word Sense Disambiguation (WSD). We have applied the "WordNet monosemous relatives" method t...
Eneko Agirre, David Martínez
ACL
2003
13 years 9 months ago
Exploiting Parallel Texts for Word Sense Disambiguation: An Empirical Study
A central problem of word sense disambiguation (WSD) is the lack of manually sense-tagged data required for supervised learning. In this paper, we evaluate an approach to automati...
Hwee Tou Ng, Bin Wang, Yee Seng Chan
AAAI
1998
13 years 8 months ago
Knowledge Lean Word-Sense Disambiguation
We present a corpus{based approach to word{sense disambiguation that only requires information that can be automatically extracted from untagged text. We use unsupervised techniqu...
Ted Pedersen, Rebecca F. Bruce
ECAI
1994
Springer
13 years 11 months ago
Interpreting Common Words in Context: a Symbolic Approach
This paper presents a lexical model dedicated to the semantic representation and interpretation of individual words in unrestricted text, where sense discrimination is difficult t...
Violaine Prince