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» Automatic Word Sense Discrimination
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110
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NAACL
2010
14 years 10 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
15 years 1 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
15 years 1 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
104
Voted
AAAI
1998
15 years 1 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
15 years 4 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