Journal Information
|
| Research Areas |
| Publication Ethics and Malpractice Statement |
| Guidelines for Authors |
| For Authors |
| Instructions to Authors |
| Copyright forms |
| Submit Manuscript |
| Call for papers |
| Guidelines for Reviewers |
| For Reviewers |
| Review Forms |
| Contacts and Support |
| Support and Contact |
| List of Issues |
| Indexing |
Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS)
ISSN:2141-7016
| Abstract: The development of mobile phone networks, video and internet technologies have created enormous pressure on the telecommunication industry. They generate and store very huge amount of data which need intelligent tools to analyze. Data mining techniques are powerful mechanisms that have different features and abilities suitable for analyzing great amount of data due to the fact that it allows the selection, exploring and modeling of large volume of dataset to uncover previously unknown data patterns for business advantage. Computational intelligence in data mining provides complementary and searching methods to solve complex and real-world problems. The aim of this paper is to explore different data mining tools and applications and how they can be used to detect telecommunication fraud, fault and improve market effectiveness. It also describes how data mining can be used to uncover useful information embedded within large datasets. |
| Keywords: computational intelligence techniques, data mining, telecommunication industry, fraud detection, fuzzy-logic |
| Download full paper |


Copyright © 2020 Journal of Emerging Trends in Engineering and Applied Sciences 2010