원문정보
보안공학연구지원센터(IJMUE)
International Journal of Multimedia and Ubiquitous Engineering
Vol.9 No.12
2014.12
pp.37-48
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
Pointing to the demand of large scale internet websites want to improve users’ loyalty and flows maintaining. A novel conception of analysis engine for massive user behavior is proposed in this paper, which combines static analysis with dynamic monitoring for user behavior. It apply some improved data mining model based on cloud computing to analysis Web log data and contextual information of the page acquired real-time. Meanwhile, using cloud database for efficient processing and storaging. The results show that this system could significantly improve the effect and efficiency of user behavior analysis.
목차
Abstract
1. Introduction
2. The Architecture of Analysis Engine
3. Research on Key Technology
3.1. Acquisition and Preprocessing of Dynamic User Behavior
3.2. Mining Historical Behavior Data
4. Experiment Results
5. Conclusion
Acknowledgements
References
1. Introduction
2. The Architecture of Analysis Engine
3. Research on Key Technology
3.1. Acquisition and Preprocessing of Dynamic User Behavior
3.2. Mining Historical Behavior Data
4. Experiment Results
5. Conclusion
Acknowledgements
References
저자정보
참고문헌
자료제공 : 네이버학술정보