Generování asociačních pravidel pro velká data

Abstract

Association rules are data analysis tool which can find relationships between objects. Shopping cart analysis for supermarket optimalization is one of the typical use cases. Volume of data for analysis is constantly growing. Older algorithms for association rules generation cannot fully utilize computational capabilities of state of the art systems and. Adjustment is required. This diploma thesis describes those algorithms and their modification for big data parallel computing.