Adding Dense, Weighted Connections to WordNet

Abstract

WORDNET, a ubiquitous tool for natural language processing, suffers from sparsity of connections between its component concepts (synsets). Through the use of human annotators, a subset of the connections between 1000 hand-chosen synsets was assigned a value of “evocation” representing how much the first concept brings to mind the second. These data, along with existing similarity measures, constitute the basis of a method for predicting evocation between previously unrated pairs. Submission Type: Long Article Topic Areas: Extending WORDNET Author of Record: Jordan Boyd-Graber, jbg@princeton.edu Under consideration for other conferences (specify)? None Adding Dense, Weighted Connections to WORDNET

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@inproceedings{BoydGraber2005AddingDW, title={Adding Dense, Weighted Connections to WordNet}, author={Jordan Boyd-Graber and Christiane Fellbaum and Daniel Osherson and Robert Schapire}, year={2005} }