Data mining aims at extraction of previously unidentified information from large databases. It can be viewed as an automated application of algorithms to discover hidden patterns a...
Data allocation is a key performance factor for parallel database systems (PDBS). This holds especially for data warehousing environments where huge amounts of data and complex an...
All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...
We describe an efficient implementation (MRDTL-2) of the Multi-relational decision tree learning (MRDTL) algorithm [23] which in turn was based on a proposal by Knobbe et al. [19] ...
One of the important problems in data mining is discovering association rules from databases of transactions where each transaction consists of a set of items. The most time consu...