Anonymization of Court Orders

Publikation: Konferencebidrag › Paper › Forskning › fagfællebedømt

Standard

Anonymization of Court Orders. / Povlsen, Claus; Jongejan, Bart; Hansen, Dorte Haltrup; Krantz Simonsen, Bo.

2016. Paper præsenteret ved Iberian Conference on Information Systems and Technologies, Spanien.

Publikation: Konferencebidrag › Paper › Forskning › fagfællebedømt

Harvard

Povlsen, C, Jongejan, B, Hansen, DH & Krantz Simonsen, B 2016, 'Anonymization of Court Orders', Paper fremlagt ved Iberian Conference on Information Systems and Technologies, Spanien, 15/06/2016 - 18/06/2016. https://doi.org/10.1109/CISTI.2016.7521611

APA

Povlsen, C., Jongejan, B., Hansen, D. H., & Krantz Simonsen, B. (2016). Anonymization of Court Orders. Paper præsenteret ved Iberian Conference on Information Systems and Technologies, Spanien. https://doi.org/10.1109/CISTI.2016.7521611

Vancouver

Povlsen C, Jongejan B, Hansen DH, Krantz Simonsen B. Anonymization of Court Orders. 2016. Paper præsenteret ved Iberian Conference on Information Systems and Technologies, Spanien. https://doi.org/10.1109/CISTI.2016.7521611

Author

Povlsen, Claus ; Jongejan, Bart ; Hansen, Dorte Haltrup ; Krantz Simonsen, Bo. / Anonymization of Court Orders. Paper præsenteret ved Iberian Conference on Information Systems and Technologies, Spanien.4 s.

Bibtex

@conference{5259240224d1469890230eff9919e0a7,
title = "Anonymization of Court Orders",
abstract = "We describe an anonymization tool that was commissioned by and specified together with Schultz, a publishing company specialized in Danish law related publications. Unavailability of training data and the need to guarantee compliance with pre-existing anonymization guidelines forced us to implement a tool using manually crafted rules. We used Bracmat, a programming language that is specialized in transforming tree data structures, to meet the requirement to pass the XML structure of the input document unscathed through the whole workflow. The tool attains a reassuringly good recall, makes almost no chunk errors and reduces the found entity designators to a nearly correct set of entities that the input text refers to, minimizing the time needed for manual check and post-editing.",
keywords = "Faculty of Humanities, Named Entity Recognition, consistent assignment, high recall rate, real life application",
author = "Claus Povlsen and Bart Jongejan and Hansen, {Dorte Haltrup} and {Krantz Simonsen}, Bo",
year = "2016",
month = jun,
doi = "10.1109/CISTI.2016.7521611",
language = "English",
note = "null ; Conference date: 15-06-2016 Through 18-06-2016",

}

RIS

TY - CONF

T1 - Anonymization of Court Orders

AU - Povlsen, Claus

AU - Jongejan, Bart

AU - Hansen, Dorte Haltrup

AU - Krantz Simonsen, Bo

N1 - Conference code: 11

PY - 2016/6

Y1 - 2016/6

N2 - We describe an anonymization tool that was commissioned by and specified together with Schultz, a publishing company specialized in Danish law related publications. Unavailability of training data and the need to guarantee compliance with pre-existing anonymization guidelines forced us to implement a tool using manually crafted rules. We used Bracmat, a programming language that is specialized in transforming tree data structures, to meet the requirement to pass the XML structure of the input document unscathed through the whole workflow. The tool attains a reassuringly good recall, makes almost no chunk errors and reduces the found entity designators to a nearly correct set of entities that the input text refers to, minimizing the time needed for manual check and post-editing.

AB - We describe an anonymization tool that was commissioned by and specified together with Schultz, a publishing company specialized in Danish law related publications. Unavailability of training data and the need to guarantee compliance with pre-existing anonymization guidelines forced us to implement a tool using manually crafted rules. We used Bracmat, a programming language that is specialized in transforming tree data structures, to meet the requirement to pass the XML structure of the input document unscathed through the whole workflow. The tool attains a reassuringly good recall, makes almost no chunk errors and reduces the found entity designators to a nearly correct set of entities that the input text refers to, minimizing the time needed for manual check and post-editing.

KW - Faculty of Humanities

KW - Named Entity Recognition

KW - consistent assignment

KW - high recall rate

KW - real life application

U2 - 10.1109/CISTI.2016.7521611

DO - 10.1109/CISTI.2016.7521611

M3 - Paper

Y2 - 15 June 2016 through 18 June 2016

ER -

ID: 164422743