Mining@home: Public Resource Computing for Distributed Data Mining

Overview

Several kinds of scientific and commercial applications require the execution of a large number of independent tasks. One highly successful and low cost mechanism for acquiring the necessary compute power for these applications is the "Public-resource computing", or "Desktop Grid" paradigm, which exploits the computational power of private computers. So far, this paradigm has not been applied to data mining applications for two main reasons. This paper focuses on one of the main data mining problem: the extraction of closed frequent itemsets from transactional databases. They show that is possible to decompose this problem into independent tasks, which however need to share a large volume of data.