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COLING
1990
13 years 6 months ago
Word Sense Disambiguation with Very Large Neural Networks Extracted from Machine Readable Dictionaries
In this paper, we describe a means for automatically building very large neural networks (VLNNs) from definition texts in machine-readable dictionaries, and demonstrate the use of...
Jean Véronis, Nancy Ide
AAAI
1998
13 years 6 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
COLING
2000
13 years 6 months ago
Identifying Terms by their Family and Friends
Multi-word terms are traditionally identified using statistical techniques or, more recently, using hybrid techniques combining statistics with shallow linguistic information. Al)...
Diana Maynard, Sophia Ananiadou
ECAI
2000
Springer
13 years 9 months ago
Enriching very large ontologies using the WWW
This paper explores the possibility to exploit text on the world wide web in order to enrich the concepts in existing ontologies. First, a method to retrieve documents from the WWW...
Eneko Agirre, Olatz Ansa, Eduard H. Hovy, David Ma...
ACL
2004
13 years 6 months ago
Unsupervised Sense Disambiguation Using Bilingual Probabilistic Models
We describe two probabilistic models for unsupervised word-sense disambiguation using parallel corpora. The first model, which we call the Sense model, builds on the work of Diab ...
Indrajit Bhattacharya, Lise Getoor, Yoshua Bengio