A Taxonomy for In-depth Evaluation of Normalization for User Generated Content

Rob van der Goot; Rik van Noord; Gertjan van Noord

A Taxonomy for In-depth Evaluation of Normalization for User Generated Content

Rob van der Goot, Rik van Noord, Gertjan van Noord

Onderzoeksoutput › Academic › peer review

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In this work we present a taxonomy of error categories for lexical normalization, which is the task of translating user generated content to canonical language. We annotate a recent normalization dataset to test the practical use of the taxonomy and read a near-perfect agreement. This annotated dataset is then used to evaluate how an existing normalization model performs on the different categories of the taxonomy. The results of this evaluation reveal that some of the problematic categories only include minor transformations, whereas most regular transformations are solved quite well.

Originele taal-2	English
Titel	LREC 2018, Eleventh International Conference on Language Resources and Evaluation
Plaats van productie	Paris
Uitgeverij	European Language Resources Association (ELRA)
Pagina's	684-688
Aantal pagina's	5
ISBN van geprinte versie	979-10-95546-00-9
Status	Published - 2018
Evenement	Eleventh International Conference on Language Resources and Evaluation - Phoenix Seagaia Resort , Miyazaki , Japan Duur: 7-mei-2018 → 12-mei-2018 http://lrec2018.lrec-conf.org/en/

Conference

Conference	Eleventh International Conference on Language Resources and Evaluation
Verkorte titel	LREC 2018
Land	Japan
Stad	Miyazaki
Periode	07/05/2018 → 12/05/2018
Internet adres	http://lrec2018.lrec-conf.org/en/

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A Taxonomy for In-depth Evaluation of Normalization for User Generated ContentFinal publisher's version, 156 KBLicentie: CC BY-NC

http://www.lrec-conf.org/proceedings/lrec2018/summaries/306.html

Taxonomy for Normalization
Goot, van der, R. (Creator) & van Noord, R. (Creator), University of Groningen, 2018
https://bitbucket.org/robvanderg/normtax
Dataset

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@inproceedings{0b6eedaa4d8447d19bf6dee124a3e98d,

title = "A Taxonomy for In-depth Evaluation of Normalization for User Generated Content",

abstract = "In this work we present a taxonomy of error categories for lexical normalization, which is the task of translating user generated content to canonical language. We annotate a recent normalization dataset to test the practical use of the taxonomy and read a near-perfect agreement. This annotated dataset is then used to evaluate how an existing normalization model performs on the different categories of the taxonomy. The results of this evaluation reveal that some of the problematic categories only include minor transformations, whereas most regular transformations are solved quite well.",

author = "{van der Goot}, Rob and {van Noord}, Rik and {van Noord}, Gertjan",

year = "2018",

language = "English",

isbn = "979-10-95546-00-9",

pages = "684--688",

booktitle = "LREC 2018, Eleventh International Conference on Language Resources and Evaluation",

publisher = "European Language Resources Association (ELRA)",

note = "Eleventh International Conference on Language Resources and Evaluation , LREC 2018 ; Conference date: 07-05-2018 Through 12-05-2018",

url = "http://lrec2018.lrec-conf.org/en/",

}

van der Goot, R, van Noord, R & van Noord, G 2018, A Taxonomy for In-depth Evaluation of Normalization for User Generated Content. in LREC 2018, Eleventh International Conference on Language Resources and Evaluation. European Language Resources Association (ELRA), Paris, blz. 684-688, Eleventh International Conference on Language Resources and Evaluation , Miyazaki , Japan, 07/05/2018. <http://www.lrec-conf.org/proceedings/lrec2018/summaries/306.html>

TY - GEN

T1 - A Taxonomy for In-depth Evaluation of Normalization for User Generated Content

AU - van der Goot, Rob

AU - van Noord, Rik

AU - van Noord, Gertjan

PY - 2018

Y1 - 2018

N2 - In this work we present a taxonomy of error categories for lexical normalization, which is the task of translating user generated content to canonical language. We annotate a recent normalization dataset to test the practical use of the taxonomy and read a near-perfect agreement. This annotated dataset is then used to evaluate how an existing normalization model performs on the different categories of the taxonomy. The results of this evaluation reveal that some of the problematic categories only include minor transformations, whereas most regular transformations are solved quite well.

AB - In this work we present a taxonomy of error categories for lexical normalization, which is the task of translating user generated content to canonical language. We annotate a recent normalization dataset to test the practical use of the taxonomy and read a near-perfect agreement. This annotated dataset is then used to evaluate how an existing normalization model performs on the different categories of the taxonomy. The results of this evaluation reveal that some of the problematic categories only include minor transformations, whereas most regular transformations are solved quite well.

M3 - Conference contribution

SN - 979-10-95546-00-9

SP - 684

EP - 688

BT - LREC 2018, Eleventh International Conference on Language Resources and Evaluation

PB - European Language Resources Association (ELRA)

CY - Paris

T2 - Eleventh International Conference on Language Resources and Evaluation

Y2 - 7 May 2018 through 12 May 2018

ER -

A Taxonomy for In-depth Evaluation of Normalization for User Generated Content

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Conference

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Datasets

Taxonomy for Normalization

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