When computationally feasible, mining extremely large databases produces tremendously
large numbers of frequent patterns. In many cases, it is impractical to mine those datasets …

In this paper, we present a tree-partition algorithm for parallel mining of frequent patterns.
Our work is based on FP-Growth algorithm, which is constituted of tree-building stage and …

Advances in computing and communication over wired and wireless networks have resulted
in many pervasive distributed computing environments. Many of these environments deal …

Association rule mining has become an essential data mining technique in various fields
and the massive growth of the available data demands more and more computational …

When computationally feasible, mining huge databases produces tremendously large
numbers of frequent patterns. In many cases, it is impractical to mine those datasets due to …

Data mining is known to be among the hottest topics in E-science. New methods for mining
vast amounts of heterogeneous data from several data sources are emerging all the time. In …

摘要在探勘關聯規則的過程中, 首先必須找出滿足最小支持度的項目組, 稱之為高頻項目組,
是探勘效率上的瓶頸所在, 因此, 如何提昇擷取高頻項目組的執行效率, 即成為探勘關聯規則最 …

Data mining is an emerging research area, whose goal is to discover potentially useful
information embedded in databases. Due to the wide availability of huge amounts of data …

Abstract Association Rule Mining (ARM) is an active data mining research area. However,
most ARM algorithms cater to a centralized environment where no external communication …

In this paper we present a coarse-grained parallel algorithm, C ONQUEST, for constructing
bounded-error summaries of high-dimensional binary attributed data in a distributed …