Data mining can extract important knowledge from large data collections - but sometimes these collections are split among various parties. Privacy concerns may prevent the parties...
Due in part to the large volume of data available today, but more importantly to privacy concerns, data are often distributed across institutional, geographical and organizational...
This paper presents a concept hierarchy-based approach to privacy preserving data collection for data mining called the P-level model. The P-level model allows data providers to d...
: Data mining is the process of posing queries and extracting patterns, often previously unknown from large quantities of data using pattern matching or other reasoning techniques....
Recently, privacy issues have become important in clustering analysis, especially when data is horizontally partitioned over several parties. Associative queries are the core retr...