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 …

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 …

Association rules are “if-then rules” with two measures which quantify the support and
confidence of the rule for a given data set. Having their origin in market basket analysis …

Sequential rule mining is an important data mining task used in a wide range of applications.
However, current algorithms for discovering sequential rules common to several sequences …

Frequent sets lie at the basis of many Data Mining algorithms. As a result, hundreds of
algorithms have been proposed in order to solve the frequent set mining problem. In this …

This paper presents and analysis the common existing sequential pattern mining algorithms.
It presents a classifying study of sequential pattern-mining algorithms into five extensive …

Progress in digital data acquisition, distribution, retrieval and storage technology has
resulted in the growth of massive databases. One of the greatest challenges facing …

Ball‐on‐ring tests have been used extensively to measure the biaxial strength of brittle
materials. However, the tests and analyses are limited to materials of uniform properties. An …

It is widely recognized that the performances of frequent-pattern mining algorithms are
closely dependent on data being handled, ie, sparse or dense. The same situation applies …

Computing frequent itemsets and maximally frequent item-sets in a database are classic
problems in data mining. The resource requirements of all extant algorithms for both …