A study on applicability of fuzzy k-member clustering to privacy preserving pattern recognition.
Hirohide KasugaiArina KawanoKatsuhiro HondaAkira NotsuPublished in: FUZZ-IEEE (2013)
Keyphrases
- privacy preserving
- pattern recognition
- clustering algorithm
- privacy preserving data mining
- multi party
- vertically partitioned data
- privacy preservation
- sensitive information
- record linkage
- data perturbation
- machine learning
- private information
- fuzzy sets
- differentially private
- preserving privacy
- data privacy
- data analysis
- feature extraction
- scalar product
- privacy sensitive