Improved Parallel Data Mining Policy for Cloud Computing Environments

DOI

10.2991/iccsae-15.2016.79How to use a DOI?

Keywords

cloud computing; data mining; Apriori algorithm; itemset.

Abstract

Cloud computing is a business model. It distributes computing tasks in a large number of computer resource pool configuration. It can provide on-demand for the user computing power, storage capacity and application services capabilities. Cloud computing offers a cheap and efficient solution for storing and analyzing massive amounts of data. Data mining is going to extract useful information and knowledge from a lot of, incomplete, noisy, fuzzy, random data to hidden practice in which people do not know in advance, but is potentially. It has played a guiding role in many fields of scientific research and business decisions ,with far-reaching social and economic significance. Data mining policy for cloud computing environments has important theoretical significance and application value. In this paper, after a series of studies in the improvement of parallel data mining algorithms can greatly improve the efficiency of data mining algorithms.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Lili Yu
AU  - Jinzhen Ping
AU  - Qian Wang
AU  - Weifeng Wang
PY  - 2016/02
DA  - 2016/02
TI  - Improved Parallel Data Mining Policy for Cloud Computing Environments
BT  - Proceedings of the 2015 5th International Conference on Computer Sciences and Automation Engineering
PB  - Atlantis Press
SP  - 414
EP  - 418
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccsae-15.2016.79
DO  - 10.2991/iccsae-15.2016.79
ID  - Yu2016/02
ER  -