Pattern mining is a core objective within data mining, involving the detection of frequent
itemsets (collections of values) within databases. This process serves to extract valuable …

Frequent itemsets mining discovers associations present among items from a large
database. However, due to privacy concerns some sensitive frequent itemsets have to be …

Frequent pattern mining aims to discover implicit, previously unknown and potentially useful
knowledge—in the form of frequently occurring sets of items—that are embedded in data …

As an important data mining and knowledge discovery task, association rule mining
searches for implicit, previously unknown, and potentially useful pieces of information—in …

Mining frequent itemsets from transactional datasets is a well known problem with good
algorithmic solutions. In the case of uncertain data, however, several new techniques have …

Concealing sensitive relationships before sharing a database is of utmost importance in
many circumstances. This implies to hide the frequent itemsets corresponding to sensitive …

Sensitive knowledge hiding is an essential requirement to prevent disclosure of any
sensitive knowledge holding in shared databases. The security of a database may be risked …

Many modern applications such as sensor networks produce probabilistic data. These data
are collected into an uncertain database. To interpret uncertainty and to mine frequent …

The concept of uncertain pattern mining was recently proposed to fulfill the demand for
processing databases with uncertain data, and various relevant methods have been …

The analysis and management of uncertain data has gained a lot of importance in the past
few years because of their importance in a wide variety of applications such as sensor …