The main purpose of data mining and analytics is to find novel, potentially useful patterns
that can be utilized in real-world applications to derive beneficial knowledge. For identifying …

The task of finding correlations between items in a dataset, association mining, has received
considerable attention over the last decade. This article presents a survey of association …

This chapter will provide a detailed survey of frequent pattern mining algorithms. A wide
variety of algorithms will be covered starting from Apriori. Many algorithms such as Eclat …

Abstract Weak isosinglet Neutral Heavy Leptons (vm) have been searched for using data
collected by the DELPHI detector corresponding to 3.3× 10 6 hadronic Z 0 decays at LEP1 …

In mining and integrating data from multiple sources, there are many privacy and security
issues. In several different contexts, the security of the full privacy-preserving data mining …

This is the first part of a large survey paper in which we analyze recent literature on Formal
Concept Analysis (FCA) and some closely related disciplines using FCA. We collected 1072 …

Frequent itemsets play an essential role in many data mining tasks that try to find interesting
patterns from databases, such as association rules, correlations, sequences, episodes …

Frequent itemset mining has been studied extensively in literature. Most previous studies
require the specification of a min/spl I. bar/support threshold and aim at mining a complete …

Security is a common problem in completely decentralized peer-to-peer systems. Although
several suggestions exist on how to create a secure key-based routing protocol, a …

Mining high utility itemsets (HUIs) from databases is an important data mining task, which
refers to the discovery of itemsets with high utilities (eg high profits). However, it may present …