A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Using BiLSTM Networks for Context-Aware Deep Sensitivity Labelling on Conversational Data
2020
Applied Sciences
Information privacy is a critical design feature for any exchange system, with privacy-preserving applications requiring, most of the time, the identification and labelling of sensitive information. However, privacy and the concept of "sensitive information" are extremely elusive terms, as they are heavily dependent upon the context they are conveyed in. To accommodate such specificity, we first introduce a taxonomy of four context classes to categorise relationships of terms with their textual
doi:10.3390/app10248924
fatcat:7azezpthcjddhe6djken52p53q