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This position paper investigates the problem of automated text anonymisation, which is a pre-requisite for secure sharing of documents con-taining sensitive information about individuals. We summarise the key concepts behind text anonymisation and provide a review of current approaches.
This paper presents a comprehensive benchmarking study comparing the performance of transformer-based models and Large Language Models(LLM) against traditional architectures for text anonymisation. Utilising the CoNLL-2003 dataset, known for its robustness and diversity, we evaluate several models.
privacy-oriented annotated text resources, making it difficult to properly evaluate the level of privacy protection offered by various anonymization methods. This paper presents TAB (Text Anonymization Benchmark), a new, open-source annotated corpus developed to address this shortage. The corpus comprises 1,268 English-language court cases ...
Text anonymisation refers to redacting - and potentially replacing - personally identifiable information (PII) within text data. Since such information is the crucial concern of data protection regulations – data is protected if and only if it can be associated with a living individual – its removal means that such data can be freely shared.
24 sie 2022 · We illustrate the use of the benchmark and the proposed metrics by assessing the empirical performance of several baseline text anonymization models. The full corpus along with its privacy ...
This position paper investigates the problem of automated text anonymisation, which is a prerequisite for secure sharing of documents containing sensitive information about individuals. We summarise the key concepts behind text anonymisation and provide a review of current approaches.
27 sie 2022 · an open-source text anonymisation tool that anonymises text data in a fully automated way. Textw ash anonymises texts in a semantically-meaningful manner, ensuring that the anonymised...
