Itemset mining is a well-known exploratory data mining technique used to discover
interesting correlations hidden in a data collection. Since it supports different targeted …

In this paper we describe a new parallel Frequent Itemset Mining algorithm called “Frontier
Expansion.” This implementation is optimized to achieve high performance on a …

In this paper we discuss the potential of cloud computing to deliver services for the study of
disasters and provide solutions for mitigation of the effects. Our investigation is focused on …

A parallel algorithm for finding the frequent itemsets in a set of transactions is presented. The
frequent individual items are identified by their index. We assume that processors number …

This paper presents an improved version of the Frequent Itemset Mining algorithm. Along
with its generalization, this algorithm for association rule discovery was designed to be used …

Frequent pattern mining (FPM) is a very important technique in data mining and has
attracted a wide range of practical applications. Equivalent Class Clustering (Eclat) has …

In this paper, we describe GPU-Eclat algorithm, a GPU (General Purpose Graphics
Processing Unit) enhanced implementation of Frequent Item set Mining (FIM). The frequent …

设计了一种基于MapReduce 框架并行挖掘大数据频繁模式的算法, 算法首先研究了运用位图
计算发现数据集频繁模式的方法; 并对传统MapReduce 框架进行扩展, 增加了位图计算和不 …