In our study, an efficient algorithm, EDMA, is proposed. It minimizes the number of candidate sets and exchange messages by local and global pruning. In local ...
Feb 20, 2018 · We implemented a distributed association rule mining algorithm on Spark named as Adaptive-Miner which uses adaptive approach for finding frequent patterns with ...
Abstract-This paper describes the alarm correlation in comm- unication networks based on data mining. A direct application of sequential algorithms to ...
Mining for a.ssociation rules between items in a large database of sales transactions has been described as an important database mining problem.
Algorithms for mining association rules from relational data have been developed. numerous query languages have been planned, to assist association rule ...
Abstract. This paper describes the issues and remedies in mining distributed databases. A direct application of sequential algorithms to.
Distributed Association Rule Mining (DARM) algorithms aim to generate rules from different datasets spread over various geographical sites; hence, they require ...
People also ask
What algorithm is used for mining association rules?
Which is an efficient algorithm for unique class association rule mining?
What is an example of an association rule in mining?
What are the advantages of association rules in data mining?
An efficient algorithm called DMA (Distributed Mining of Association rules), which generates a small number of candidate sets and requires only O(n) ...
Recently, as the need to mine patterns across distributed databases has grown, Distributed Association Rule Mining (D-ARM) algorithms have been developed.
In this study, an efficient algorithm, DMA, is proposed. It generates a small number of candidate sets and requires only O(n) messages for support count ...