Frequent itemset mining (FIM) is an essential task within data analysis since it is responsible
for extracting frequently occurring events, patterns, or items in data. Insights from such …

Frequent pattern mining has been a focused theme in data mining research for over a
decade. Abundant literature has been dedicated to this research and tremendous progress …

With the growing popularity of shared resources, large volumes of complex data of different
types are collected automatically. Traditional data mining algorithms generally have …

Data Mining: Concepts and Techniques, Fourth Edition introduces concepts, principles, and
methods for mining patterns, knowledge, and models from various kinds of data for diverse …

Association rule discovery has emerged as an important problem in knowledge discovery
and data mining. The association mining task consists of identifying the frequent itemsets …

Data mining can extract important knowledge from large data collections ut sometimes these
collections are split among various parties. Privacy concerns may prevent the parties from …

Privacy preserving mining of distributed data has numerous applications. Each application
poses different constraints: What is meant by privacy, what are the desired results, how is the …

Content-Centric Networking (CCN) is an emerging networking paradigm being considered
as a possible replacement for the current IP-based host-centric Internet infrastructure. CCN …

We provide here an overview of the new and rapidly emerging research area of privacy
preserving data mining. We also propose a classification hierarchy that sets the basis for …

In this paper, we provide the preliminaries of basic concepts about association rule mining
and survey the list of existing association rule mining techniques. Of course, a single article …