anonymizer universal windows cleanup utility

#Anonymizer universal windows cleanup utility keygen#

We illustrate the use of the benchmark and the proposed metrics by assessing the empirical performance of several baseline text anonymization models. Along with presenting the corpus and its annotation layers, we also propose a set of evaluation metrics that are specifically tailored towards measuring the performance of text anonymization, both in terms of privacy protection and utility preservation. Compared to previous work, the TAB corpus is designed to go beyond traditional de-identification (which is limited to the detection of predefined semantic categories), and explicitly marks which text spans ought to be masked in order to conceal the identity of the person to be protected.

#Anonymizer universal windows cleanup utility keygen#

The corpus comprises 1,268 English-language court cases from the European Court of Human Rights (ECHR) enriched with comprehensive annotations about the personal information appearing in each document, including their semantic category, identifier type, confidential attributes, and co-reference relations. This paper presents TAB (Text Anonymization Benchmark), a new, open-source annotated corpus developed to address this shortage. Text anonymization, defined as the task of editing a text document to prevent the disclosure of personal information, currently suffers from a shortage of privacy-oriented annotated text resources, making it difficult to properly evaluate the level of privacy protection offered by various anonymization methods. We present a novel benchmark and associated evaluation metrics for assessing the performance of text anonymization methods.