Preservation of confidential information privacy and association rule hiding for data mining: a bibliometric review
In this era of technology, data of business organizations are growing with acceleration. Mining hidden patterns from this huge database would benefit many industries improving their decision-making processes. Along with the non-sensitive information, these databases also contain some sensitive infor...
- Autores:
-
Silva, Jesus
Cubillos, Jenny
Vargas Villa, Jesus
Romero, Ligia
Solano, Darwin
Fernández, Claudia
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2019
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/4837
- Acceso en línea:
- https://hdl.handle.net/11323/4837
https://repositorio.cuc.edu.co/
- Palabra clave:
- confidential information privacy preservation
approaches to hiding of association rules of data
bibliometric analysis
SCOPUS
- Rights
- openAccess
- License
- Attribution-NonCommercial-NoDerivatives 4.0 International