Mining Association Rules in Various Computing Environments: A Survey
June 30, 2019 ยท The Cartographer ยท ๐ arXiv.org
"No code URL or promise found in abstract"
"Title-pattern auto-detect: Mining Association Rules in Various Computing Environments: A Survey"
Evidence collected by the PWNC Scanner
Authors
Sudhakar Singh, Pankaj Singh, Rakhi Garg, P. K. Mishra
arXiv ID
1908.07918
Category
cs.DC: Distributed Computing
Cross-listed
cs.DB,
cs.LG
Citations
7
Venue
arXiv.org
Last Checked
3 days ago
Abstract
Association Rule Mining (ARM) is one of the well know and most researched technique of data mining. There are so many ARM algorithms have been designed that their counting is a large number. In this paper we have surveyed the various ARM algorithms in four computing environments. The considered computing environments are sequential computing, parallel and distributed computing, grid computing and cloud computing. With the emergence of new computing paradigm, ARM algorithms have been designed by many researchers to improve the efficiency by utilizing the new paradigm. This paper represents the journey of ARM algorithms started from sequential algorithms, and through parallel and distributed, and grid based algorithms to the current state-of-the-art, along with the motives for adopting new machinery.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Distributed Computing
R.I.P.
๐ป
Ghosted
R.I.P.
๐ป
Ghosted
Reproducing GW150914: the first observation of gravitational waves from a binary black hole merger
R.I.P.
๐ป
Ghosted
MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems
R.I.P.
๐ป
Ghosted
Efficient Architecture-Aware Acceleration of BWA-MEM for Multicore Systems
R.I.P.
๐ป
Ghosted
Adaptive Federated Learning in Resource Constrained Edge Computing Systems
R.I.P.
๐ป
Ghosted