A Fast Distributed Mining of Association Rules in Horizontally Distributed Database

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Provided by: The International Journal of Innovative Research in Computer and Communication Engineering
Topic: Big Data
Format: PDF
Data mining can extract important knowledge from large data collections, but sometimes these collections are split among various parties. This paper addresses a fast distributed mining of association rules over horizontally distributed data. While preparing a data set for analysis is generally the most time consuming task in a data mining, requiring numerous complex SQL queries, joining tables and aggregating columns. Existing SQL aggregations have limitations to prepare data sets because they return one column per aggregated group.
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