OcrV1, PascalFrancis, Corpus, bibRecord, 000725

OCRSpell: an interactive spelling correction system for OCR errors in text

Identifieur interne : 000725 ( PascalFrancis/Corpus ); précédent : 000724; suivant : 000726

OCRSpell: an interactive spelling correction system for OCR errors in text

Auteurs : Kazem Taghva ; Eric Stofsky

Source :

International journal on document analysis and recognition : (Print) [ 1433-2833 ] ; 2001.

RBID : Pascal:01-0203395

Descripteurs français

Pascal (Inist)
- Reconnaissance caractère, Assistance orthographique, Système conversationnel, Didacticiel, Apprentissage(intelligence artificielle), Estimation Bayes, Analyse statistique, Texte, Multiplicité, Recherche information, Correction erreur, Balayage, Reconnaissance optique caractère, Système correction orthographe.

English descriptors

KwdEn :
- Bayes estimation, Character recognition, Educational software program, Error correction, Information retrieval, Interactive system, Learning (artificial intelligence), Multiplicity, Optical character recognition, Scanning, Spelling aids, Statistical analysis, Text.

Abstract

In this paper, we describe a spelling correction system designed specifically for OCR-generated text that selects candidate words through the use of information gathered from multiple knowledge sources. This system for text correction is based on static and dynamic device mappings, approximate string matching, and n-gram analysis. Our statistically based, Bayesian system incorporates a learning feature that collects confusion information at the collection and document levels. An evaluation of the new system is presented as well.

Notice en format standard (ISO 2709)

Pour connaître la documentation sur le format Inist Standard.

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A03		`1`		`@0 Int. j. doc. anal. recognit. : (Print)`
A05				`@2 3`
A06				`@2 3`
A08	`01`	`1`	`ENG`	`@1 OCRSpell: an interactive spelling correction system for OCR errors in text`
A11	`01`	`1`		`@1 TAGHVA (Kazem)`
A11	`02`	`1`		`@1 STOFSKY (Eric)`
A14	`01`			`@1 Information Science Research Institute, University of Nevada @2 Las Vegas, Las Vegas, NV 89154-4021 @3 USA @Z 1 aut. @Z 2 aut.`
A20				`@1 125-137`
A21				`@1 2001`
A23	`01`			`@0 ENG`
A43	`01`			`@1 INIST @2 26790 @5 354000097506710010`
A44				`@0 0000 @1 © 2001 INIST-CNRS. All rights reserved.`
A45				`@0 27 ref.`
A47	`01`	`1`		`@0 01-0203395`
A60				`@1 P`
A61				`@0 A`
A64	`01`	`1`		`@0 International journal on document analysis and recognition : (Print)`
A66	`01`			`@0 DEU`
C01	`01`		`ENG`	@0 In this paper, we describe a spelling correction system designed specifically for OCR-generated text that selects candidate words through the use of information gathered from multiple knowledge sources. This system for text correction is based on static and dynamic device mappings, approximate string matching, and n-gram analysis. Our statistically based, Bayesian system incorporates a learning feature that collects confusion information at the collection and document levels. An evaluation of the new system is presented as well.
C02	`01`	`X`		`@0 001D02C03`
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C03	`01`	`X`	`ENG`	`@0 Character recognition @5 01`
C03	`01`	`X`	`SPA`	`@0 Reconocimiento carácter @5 01`
C03	`02`	`3`	`FRE`	`@0 Assistance orthographique @5 02`
C03	`02`	`3`	`ENG`	`@0 Spelling aids @5 02`
C03	`03`	`X`	`FRE`	`@0 Système conversationnel @5 03`
C03	`03`	`X`	`ENG`	`@0 Interactive system @5 03`
C03	`03`	`X`	`SPA`	`@0 Sistema conversacional @5 03`
C03	`04`	`X`	`FRE`	`@0 Didacticiel @5 04`
C03	`04`	`X`	`ENG`	`@0 Educational software program @5 04`
C03	`04`	`X`	`SPA`	`@0 Programa didactico @5 04`
C03	`05`	`3`	`FRE`	`@0 Apprentissage(intelligence artificielle) @5 05`
C03	`05`	`3`	`ENG`	`@0 Learning (artificial intelligence) @5 05`
C03	`06`	`X`	`FRE`	`@0 Estimation Bayes @5 06`
C03	`06`	`X`	`ENG`	`@0 Bayes estimation @5 06`
C03	`06`	`X`	`SPA`	`@0 Estimación Bayes @5 06`
C03	`07`	`X`	`FRE`	`@0 Analyse statistique @5 07`
C03	`07`	`X`	`ENG`	`@0 Statistical analysis @5 07`
C03	`07`	`X`	`SPA`	`@0 Análisis estadístico @5 07`
C03	`08`	`X`	`FRE`	`@0 Texte @5 08`
C03	`08`	`X`	`ENG`	`@0 Text @5 08`
C03	`08`	`X`	`SPA`	`@0 Texto @5 08`
C03	`09`	`X`	`FRE`	`@0 Multiplicité @5 09`
C03	`09`	`X`	`ENG`	`@0 Multiplicity @5 09`
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C03	`10`	`X`	`FRE`	`@0 Recherche information @5 10`
C03	`10`	`X`	`ENG`	`@0 Information retrieval @5 10`
C03	`10`	`X`	`SPA`	`@0 Recuperación información @5 10`
C03	`11`	`X`	`FRE`	`@0 Correction erreur @5 11`
C03	`11`	`X`	`ENG`	`@0 Error correction @5 11`
C03	`11`	`X`	`SPA`	`@0 Corrección error @5 11`
C03	`12`	`X`	`FRE`	`@0 Balayage @5 12`
C03	`12`	`X`	`ENG`	`@0 Scanning @5 12`
C03	`12`	`X`	`SPA`	`@0 Exploración @5 12`
C03	`13`	`X`	`FRE`	`@0 Reconnaissance optique caractère @5 13`
C03	`13`	`X`	`ENG`	`@0 Optical character recognition @5 13`
C03	`13`	`X`	`SPA`	`@0 Reconocimento óptico de caracteres @5 13`
C03	`14`	`X`	`FRE`	`@0 Système correction orthographe @4 INC @5 82`
N21				`@1 141`

Format Inist (serveur)

NO :	PASCAL 01-0203395 INIST
ET :	OCRSpell: an interactive spelling correction system for OCR errors in text
AU :	TAGHVA (Kazem); STOFSKY (Eric)
AF :	Information Science Research Institute, University of Nevada/Las Vegas, Las Vegas, NV 89154-4021/Etats-Unis (1 aut., 2 aut.)
DT :	Publication en série; Niveau analytique
SO :	International journal on document analysis and recognition : (Print); ISSN 1433-2833; Allemagne; Da. 2001; Vol. 3; No. 3; Pp. 125-137; Bibl. 27 ref.
LA :	Anglais
EA :	In this paper, we describe a spelling correction system designed specifically for OCR-generated text that selects candidate words through the use of information gathered from multiple knowledge sources. This system for text correction is based on static and dynamic device mappings, approximate string matching, and n-gram analysis. Our statistically based, Bayesian system incorporates a learning feature that collects confusion information at the collection and document levels. An evaluation of the new system is presented as well.
CC :	001D02C03
FD :	Reconnaissance caractère; Assistance orthographique; Système conversationnel; Didacticiel; Apprentissage(intelligence artificielle); Estimation Bayes; Analyse statistique; Texte; Multiplicité; Recherche information; Correction erreur; Balayage; Reconnaissance optique caractère; Système correction orthographe
ED :	Character recognition; Spelling aids; Interactive system; Educational software program; Learning (artificial intelligence); Bayes estimation; Statistical analysis; Text; Multiplicity; Information retrieval; Error correction; Scanning; Optical character recognition
SD :	Reconocimiento carácter; Sistema conversacional; Programa didactico; Estimación Bayes; Análisis estadístico; Texto; Multiplicidad; Recuperación información; Corrección error; Exploración; Reconocimento óptico de caracteres
LO :	INIST-26790.354000097506710010
ID :	01-0203395

Links to Exploration step

Pascal:01-0203395

Le document en format XML

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<front><div type="abstract" xml:lang="en">In this paper, we describe a spelling correction system designed specifically for OCR-generated text that selects candidate words through the use of information gathered from multiple knowledge sources. This system for text correction is based on static and dynamic device mappings, approximate string matching, and n-gram analysis. Our statistically based, Bayesian system incorporates a learning feature that collects confusion information at the collection and document levels. An evaluation of the new system is presented as well.</div>
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<ET>OCRSpell: an interactive spelling correction system for OCR errors in text</ET>
<AU>TAGHVA (Kazem); STOFSKY (Eric)</AU>
<AF>Information Science Research Institute, University of Nevada/Las Vegas, Las Vegas, NV 89154-4021/Etats-Unis (1 aut., 2 aut.)</AF>
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<EA>In this paper, we describe a spelling correction system designed specifically for OCR-generated text that selects candidate words through the use of information gathered from multiple knowledge sources. This system for text correction is based on static and dynamic device mappings, approximate string matching, and n-gram analysis. Our statistically based, Bayesian system incorporates a learning feature that collects confusion information at the collection and document levels. An evaluation of the new system is presented as well.</EA>
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OCRSpell: an interactive spelling correction system for OCR errors in text

OCRSpell: an interactive spelling correction system for OCR errors in text

Source :

Descripteurs français

English descriptors

Abstract

Notice en format standard (ISO 2709)

Format Inist (serveur)

Links to Exploration step

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

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