Adding dense, weighted connections to WordNet

Jordan Boyd-Graber; Christiane Fellbaum; Daniel Osherson; Robert Schapire

Adding dense, weighted connections to WordNet

Jordan Boyd-Graber, Christiane Fellbaum, Daniel Osherson, Robert Schapire

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English (US)
Title of host publication	GWC 2006
Subtitle of host publication	3rd International Global WordNet Conference, Proceedings
Publisher	Masaryk University
Pages	29-35
Number of pages	7
ISBN (Print)	8021039159, 9788021039155
State	Published - 2005
Event	3rd International Global WordNet Conference, GWC 2006 - Jeju Island, Korea, Republic of Duration: Jan 22 2006 → Jan 26 2006

Publication series

Name	GWC 2006: 3rd International Global WordNet Conference, Proceedings

Other

Other	3rd International Global WordNet Conference, GWC 2006
Country/Territory	Korea, Republic of
City	Jeju Island
Period	1/22/06 → 1/26/06

All Science Journal Classification (ASJC) codes

Language and Linguistics
Literature and Literary Theory

Cite this

@inproceedings{f47895ce0ff749618a360186b065556d,

title = "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.",

author = "Jordan Boyd-Graber and Christiane Fellbaum and Daniel Osherson and Robert Schapire",

year = "2005",

language = "English (US)",

isbn = "8021039159",

series = "GWC 2006: 3rd International Global WordNet Conference, Proceedings",

publisher = "Masaryk University",

pages = "29--35",

booktitle = "GWC 2006",

note = "3rd International Global WordNet Conference, GWC 2006 ; Conference date: 22-01-2006 Through 26-01-2006",

}

Boyd-Graber, J, Fellbaum, C, Osherson, D & Schapire, R 2005, Adding dense, weighted connections to WordNet. in GWC 2006: 3rd International Global WordNet Conference, Proceedings. GWC 2006: 3rd International Global WordNet Conference, Proceedings, Masaryk University, pp. 29-35, 3rd International Global WordNet Conference, GWC 2006, Jeju Island, Korea, Republic of, 1/22/06.

Adding dense, weighted connections to WordNet. / Boyd-Graber, Jordan; Fellbaum, Christiane; Osherson, Daniel et al.
GWC 2006: 3rd International Global WordNet Conference, Proceedings. Masaryk University, 2005. p. 29-35 (GWC 2006: 3rd International Global WordNet Conference, Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Adding dense, weighted connections to WordNet

AU - Boyd-Graber, Jordan

AU - Fellbaum, Christiane

AU - Osherson, Daniel

AU - Schapire, Robert

PY - 2005

Y1 - 2005

N2 - 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.

AB - 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.

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M3 - Conference contribution

AN - SCOPUS:84904631264

SN - 8021039159

SN - 9788021039155

T3 - GWC 2006: 3rd International Global WordNet Conference, Proceedings

SP - 29

EP - 35

BT - GWC 2006

PB - Masaryk University

T2 - 3rd International Global WordNet Conference, GWC 2006

Y2 - 22 January 2006 through 26 January 2006

ER -

Adding dense, weighted connections to WordNet

Abstract

Publication series

Other

All Science Journal Classification (ASJC) codes

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