Konferensartikel

AnonyMate: A Toolkit for Anonymizing Unstructured Chat Data

Allison Adams
Artificial Solutions, Stureplan 15, 111 45 Stockholm, Sweden

Eric Aili
Artificial Solutions, Stureplan 15, 111 45 Stockholm, Sweden

Daniel Aioanei
Artificial Solutions, Stureplan 15, 111 45 Stockholm, Sweden

Rebecca Jonsson
Artificial Solutions, Stureplan 15, 111 45 Stockholm, Sweden

Lina Mickelsson
Artificial Solutions, Stureplan 15, 111 45 Stockholm, Sweden

Dagmar Mikmekova
Artificial Solutions, Stureplan 15, 111 45 Stockholm, Sweden

Fred Roberts
Artificial Solutions, Stureplan 15, 111 45 Stockholm, Sweden

Javier Fernandez Valencia
Artificial Solutions, Stureplan 15, 111 45 Stockholm, Sweden

Roger Wechsler
Artificial Solutions, Stureplan 15, 111 45 Stockholm, Sweden

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Ingår i: Proceedings of the Workshop on NLP and Pseudonymisation, September 30, 2019, Turku, Finland

Linköping Electronic Conference Proceedings 166:1, s. 1-7

NEALT Proceedings Series 41:1, s. 1-7

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Publicerad: 2019-09-30

ISBN: 978-91-7929-996-5

ISSN: 1650-3686 (tryckt), 1650-3740 (online)

Abstract

Most existing research on the automatic anonymization of text data has been limited to the de-identification of medical records. This is beginning to change following the passage of GDPR privacy laws, which have made the task of automatic text anonymization more relevant than ever. We present our privacy protection toolkit, AnonyMate, which is built to anonymize both personal identifying information (PII) as well as corporate identifying information (CII) in human-computer dialogue text data.

Nyckelord

Anonymization, GDPR, Human-Computer Dialogue Data, Named Entity Recognition

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