Ubiquitous Environment for Data Stream Mining : A Survey

Jagruti D. Parmar, Jalpa T. Patel

Abstract


Ubiquitous Data Mining (UDM) is a recent research topic that uses data mining techniques to extract useful knowledge from data continuously generated from devices with limited computational resources that move in time and space, namely when its characteristics reflect a World in Movement. UDM is the time-critical process of pattern discovery in data streams in a wireless environment. Data Stream Mining is defined as the process of extracting knowledge structures from continuous-rapid datasets. This paper presents overview of data stream mining. And also discuss issues and challenges for data stream mining ubiquitous environment. In short, this paper goal is to provide full knowledge of data stream mining in the ubiquitous environment.

Full Text:

PDF

References


Mohamed Medhat Gaber, Shonali Krishnaswamy, Arkady Zaslavsky, ” Ubiquitous Data Stream Mining”, Proceeding of Current Research and Future Directions Workshop Proceedings, held in conjunction with the Eighth Pacific-Asia Conferences on Knowledge Discovery and Data Mining, Australia, Sydney (2004): 1-10.

Mohamed Medhat Gaber, Arkady Zaslavsky, and Shonali Krishnaswamy, “39. Data Stream Mining”, O. Maimon, L. Rokach (eds.), Data Mining and Knowledge Discovery Handbook, 2nd ed., Springer Science+Business Media, LLC (2010): 759-787.

Vishal Meshram, Vidula Meshram and Kailas Patil, “A Survey on Ubiquitous Computing”, ICTACT Journal On Soft Computing, Volume: 06, Issue: 02 (2016): 1130-1135.

Mohamed Medhat Gaber, Joa˜o Gama, Shonali Krishnaswamy, Joa˜o Ba´ rtolo Gomes and Frederic Stahl, “Data stream mining in ubiquitous environments: state-of-the-art and current directions”, John Wiley & Sons, Ltd., Volume 4, March/April ( 2014): 116-138.

Jo˜ao B´artolo Gomes, Ernestina Menasalvas and Pedro A. C. Sousa, “Situation-Aware Data Stream Mining Service for Ubiquitous Applications”, Eleventh International Conference on Mobile Data Management, IEEE Computer Society (2010):360-365.

Younghee Kim, Youngju Noh, Wonyoung Kim, Junsuk Ryu, Ungmo Kim, “A False Negative Oriented Approach for Efficient Data Stream Analysis in Ubiquitous Environment”, IEEE (2009).

Iti Agarwal, Shonali Krishnaswamy and Mohamed Medhat Gaber, “Resource-Aware Ubiquitous Data Stream Querying”, Proceedings of the International Conference on Information and Automation, December 15-18, Colombo, Sri Lanka (2005): 1-8.

Katharina Morik, Felix Jungermann, Nico Piatkowski and Michael Engel, “Enhancing Ubiquitous Systems Through System Call Mining”, IEEE Computer Society, International Conference on Data Mining Workshops (2010): 1338-1345.

GU Jinan, LI Guojing, “Study on the Data Stream Mining and Its Application Facing the Mobile Environment”, Applied Mechanics and Materials , Trans Tech Publications, Switzerland , Vol 43 (2011): 695-698.

Joao Bartolo Gomes, Shonali Krishnaswamy, Mohamed M. Gaber, Pedro A.C. Sousa, and Ernestina Menasalvas, “Mobile Activity Recognition Using Ubiquitous Data Stream Mining”, Springer-Verlag Berlin Heidelberg, A. Cuzzocrea and U. Dayal (Eds.) DaWaK, LNCS 7448 (2012): 130–141.




DOI: https://doi.org/10.23956/ijarcsse.v8i7.820

Refbacks

  • There are currently no refbacks.




© International Journals of Advanced Research in Computer Science and Software Engineering (IJARCSSE)| All Rights Reserved | Powered by Advance Academic Publisher.