The week's pick
Random Articles
Reseach Article
An Overview on Mobile Data Mining
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 99 - Number 12 |
| Year of Publication: 2014 |
| Authors: D. Natarajasivan, M. Govindarajan |
10.5120/17424-8277
|
D. Natarajasivan, M. Govindarajan . An Overview on Mobile Data Mining. International Journal of Computer Applications. 99, 12 ( August 2014), 11-14. DOI=10.5120/17424-8277
Abstract
In early days the mobile phones are considered to perform only telecommunication operation. This scenario of mobile phones as communication devices changed with the emergence of a new class of mobile devices called the smart phones. These smart phones in addition to being used as a communication device are capable of doing things that a computer does. In recent times the smart phone are becoming more and more powerful in both computing and storage aspects. The data generated by the smart phone provide a means to get new knowledge about various aspects like usage, movement of the user etc. This paper provides an introduction to Mobile Data Mining and its types.
References
- NeelamadhabPadhy, Pragnyaban Mishra, RasmitaPanigrahi. 2012. The Survey of Data Mining Applications and Feature Scope. In International Journal of Computer Science, Engineering and Information Technology, Vol. 2, No. 3, 43-58.
- Le-Hung Tran, Michele Catasta, Luke K. McDowell, Karl Aberer. 2012. Next Place Prediction using Mobile Data. In Mobile Data Challenge 2012 (by Nokia), Newcastle.
- Jingjing Wang, BhaskarPrabhala. 2012. Periodicity Based Next Place Prediction. In: Mobile Data Challenge 2012 (by Nokia), Newcastle.
- Seyed Hasan Mortazavi Zarch, Farhad Jalilzadeh, Madihesadat Yazdanivaghef. 2012. Data Mining For Intrusion Detection in Mobile Systems. In IOSR Journal of Computer Engineerin, Vol. 6, 42-47.
- Eric Hsueh-Chan Lu, Vincent S. Tseng, Philip S. Yu. 2011. Mining Cluster-Based Temporal Mobile Sequential Patterns in Location-Based Service Environments. In IEEE Transactions On Knowledge And Data Engineering, Vol. 23, 914-925.
- GokulChittaranjan, Jan Blom, DanielGatica-Perez. 2011. Mining large-scale smartphone data for personality studies. In Personal and Ubiquitous Computing.
- H. Cao, T. Bao, Q. Yang, E. Chen, and J. Tian. 2010. An effective approach for mining mobile user habits. In CIKM'10, 1677–1680.
- Bharat Kumar Addagada. 2010. Intrusion Detection in Mobile Phone Systems Using Data Mining Techniques. M. Sc. Thesis, Iowa State University, Ames, Iowa.
- KoenSmets, Brigitte Verdonk, Elsa M. Jordaan. 2009. Discovering Novelty in Spatio/Temporal Data Using One-Class Support Vector Machines. In IJCNN.
- Thi Hong Nhan Vu, Jun Wook Lee, and Keun Ho Ryu. 2008. Spatiotemporal Pattern Mining Technique for Location-Based Service System, In ETRI Journal, Vol. 30, 421-431.
- GyozoGidofalvi. 2007. Spatio–Temporal Data Mining for Location–Based Services, Ph. D. Thesis, Aalborg University, Denmark.
- Fosca Giannotti, Mirco Nanni, Fabio Pinelli , Dino Pedreschi. 2007. Trajectory pattern mining. In Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining.
- GokhanYavas, DimitriosKatsaros, OzgurUlusoy, YannisManolopoulos. 2005. A data mining approach for location prediction in mobile environments. In Data & Knowledge Engineering, Elsevier, 121-146.
- Qiankun Zhao, Sourav S. Bhowmick. 2003. Association Rule Mining: A Survey. In Technical Report, CAIS, Nanyang Technological University.
- Jae Du Chung, Ok Hyun Paek, JunWook Lee, Keun Ho Ryu. 2002. Temporal Pattern Mining of Moving Objects for Location-Based Service. In LNCS Springer, 331-340.
- RakeshAgrawal, RamakrishnanSrikant. 1995. Mining Sequential Patterns. In ICIDE, 3-14.
Index Terms
Keywords