Anonymization For Text Data
Anonymization for Text Data is a data protection technique that belongs to the class of anonymization methods and specifically involves the systematic removal, replacement, or obfuscation of personally identifiable information and other sensitive attributes in unstructured textual content to prevent re-identification while preserving the utility of the original text for analysis.
44
Publications
1.6K
Citations
131
Authors
83
Institutions
Publications per year
2017–2026
24
Parents
44
A dummy-based user privacy protection approach for text information retrieval
Zongda Wu, Shigen Shen, Xinze Lian et al. · Knowledge-Based Systems · 2020 · 152 citations
Using TF-IDF to hide sensitive itemsets
Tzung‐Pei Hong, Jerry Chun‐Wei Lin, Kuo-Tung Yang et al. · Applied Intelligence · 2012 · 118 citations
1–5 of 44
131
5
h-index
3
h-index
3
h-index
3
h-index
3
h-index
1–5 of 131
83

Universitat Rovira i Virgili
Tarragona, Spain
5 h-index
14 publications
577 citations
Arizona State University
Tempe, United States
3 h-index
10 publications
417 citations

University of Waterloo
Waterloo, Canada
3 h-index
3 publications
67 citations
IBM (United States)
Armonk, United States
2 h-index
3 publications
50 citations
Purdue University West Lafayette
West Lafayette, United States
2 h-index
6 publications
240 citations
Carnegie Mellon University
Pittsburgh, United States
2 h-index
4 publications
115 citations

Pennsylvania State University
State College, United States
2 h-index
2 publications
50 citations
University of Cambridge
Cambridge, United Kingdom
1 h-index
1 publications
26 citations
1–8 of 83
Repository · 4 publications · 82 citations
4
h-index
Repository · 1 publications · 22 citations
1
h-index
1 publications · 20 citations
1
h-index
1 publications · 17 citations
1
h-index
1 publications · 18 citations
1
h-index
1–5