A framework for data mining and knowledge discovery in cloud computing
| dc.contributor.author | Birant D. | |
| dc.contributor.author | Yildirim P. | |
| dc.date.accessioned | 2024-07-22T08:12:07Z | |
| dc.date.available | 2024-07-22T08:12:07Z | |
| dc.date.issued | 2016 | |
| dc.description.abstract | The massive amounts of data being generated in the current world of information technology have increased from terabytes to petabytes in volume. The fact that extracting knowledge from large-scale data is a challenging issue creates a great demand for cloud computing because of its potential benefits such as scalable storage and processing services. Considering this motivation, this chapter introduces a novel framework, data mining in cloud computing (DMCC), that allows users to apply classification, clustering, and association rule mining methods on huge amounts of data efficiently by combining data mining, cloud computing, and parallel computing technologies. The chapter discusses the main architectural components, interfaces, features, and advantages of the proposed DMCC framework. This study also compares the running times when data mining algorithms are executed in serial and parallel in a cloud environment through DMCC framework. Experimental results show that DMCC greatly decreases the execution times of data mining algorithms. © Springer International Publishing Switzerland 2016. All rights reserved. | |
| dc.identifier.DOI-ID | 10.1007/978-3-319-31861-5_11 | |
| dc.identifier.uri | http://akademikarsiv.cbu.edu.tr:4000/handle/123456789/15928 | |
| dc.language.iso | English | |
| dc.publisher | Springer International Publishing | |
| dc.subject | Association rules | |
| dc.subject | Classification (of information) | |
| dc.subject | Cloud computing | |
| dc.subject | Data reduction | |
| dc.subject | Digital storage | |
| dc.subject | Architectural components | |
| dc.subject | Association rule mining methods | |
| dc.subject | Clustering | |
| dc.subject | Data mining algorithm | |
| dc.subject | Data mining and knowledge discovery | |
| dc.subject | DMCC | |
| dc.subject | Parallel com- puting | |
| dc.subject | Potential benefits | |
| dc.subject | Data mining | |
| dc.title | A framework for data mining and knowledge discovery in cloud computing | |
| dc.type | Book chapter |