Data Partitioning and Association Rule Mining Using a Multi-Agent System

Provided by: IJESIT
Topic: Data Management
Format: PDF
In this paper the author explores and demonstrates (by experiment) the capabilities of Multi-Agent Data Mining (MADM) System in the context of parallel and distributed Data Mining (DM). The exploration is conducted by considering a specific parallel/distributed DM scenario, namely data (vertical/horizontal) partitioning to achieve parallel/distributed ARM. To facilitate the partitioning a compressed set enumeration tree data structure (the T-tree) is used together with an associated ARM algorithm (Apriori-T). The aim of the scenario is to demonstrate that the MADM vision is capable of exploiting the benefits of parallel computing; particularly parallel query processing and parallel data accessing.

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