CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Big Data for Education in Students� Perspective

Published on February 2015 by G. Vaitheeswaran, L. Arockiam
journal_cover_thumbnail

Advanced Computing and Communication Techniques for High Performance Applications
Foundation of Computer Science USA
ICACCTHPA2014 - Number 4
February 2015
Authors: G. Vaitheeswaran, L. Arockiam
a0929dba-9c50-4331-ad7a-a2a0301a94d1

G. Vaitheeswaran, L. Arockiam . Big Data for Education in Students� Perspective. Advanced Computing and Communication Techniques for High Performance Applications. ICACCTHPA2014, 4 (February 2015), 11-17.

@article{
author = { G. Vaitheeswaran, L. Arockiam },
title = { Big Data for Education in Students� Perspective },
journal = { Advanced Computing and Communication Techniques for High Performance Applications },
issue_date = { February 2015 },
volume = { ICACCTHPA2014 },
number = { 4 },
month = { February },
year = { 2015 },
issn = 0975-8887,
pages = { 11-17 },
numpages = 7,
url = { /proceedings/icaccthpa2014/number4/19454-6041/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 Advanced Computing and Communication Techniques for High Performance Applications
%A G. Vaitheeswaran
%A L. Arockiam
%T Big Data for Education in Students� Perspective
%J Advanced Computing and Communication Techniques for High Performance Applications
%@ 0975-8887
%V ICACCTHPA2014
%N 4
%P 11-17
%D 2015
%I International Journal of Computer Applications
Abstract

Big Data Analytics is the new technology for extracting hidden information from the large datasets or data deluge, due to its volume, variety, and velocity. This paper presents the overview of big data, its available technologies and tools and discusses the open issues of big data. Big data plays a significant role in education sector. Everything has become digitalized in the educational institutions, which leads to store and process enormous amount of data. Handling the huge amount of data is complex. The main focus of this paper is to propose a new approach to analyze the large streaming data that produced by web server logs of educational institution. The result represents the student's web usage behavior, which supports to make better decisions to improve the student's performance and suggest recommendations for their academic perspectives.

References
  1. https://www. ida. gov. sg/~/media/Files/InfocommLandscape/Technology/TechnologyRoadmap/BigData. pdf, as on 08-5-2014
  2. IDC. the 2011 Digital Universe Study: Extracting Value from Chaos, http://www. emc. com/collateral/analyst-reports/idc-extracting-value-from-chaos-ar. pdf, as on 08-05-2014.
  3. Gartner, http://www. gartner. com/it-glossary/bigdata
  4. Infocomm Development Authority of Singapore, "Big Data", 30, Nov 2012.
  5. Jiawei Han and Micheline Kamber, "Data Mining Concepts and Techniques", chapter - 1
  6. D. Pratiba, G. Shobha, "Educational BigData Mining Approach in Cloud: Reviewing the Trend", IJCA (0975 – 8887), Volume 92 – No. 13, April 2014.
  7. R. Sallam, M. Beyer, N. Heudecker, "Key Trends in Big Data Technologies, An Article from the Connected Buisness", 2013.
  8. http://httpd. apache. org/docs/current/logs. html, internet source as on 07/05/2014.
  9. L. K. Joshila Grace, V. Maheswari, Dhinaharan Nagamalai, "Analysis of Web Logs and Web User in Web Mining", International Journal of Network Security & Its Applications", IJNSA, Vol. 3, No. 1, January 2011.
  10. A. Bifet, G. Holmes, R. Kirkby, and B. Pfahringer. MOA: Massive Online Analysis http://moa. cms. waikato. ac. nz/. Journal of Machine Learning Research (JMLR), 2010.
  11. L. K. Joshila Grace, V. Maheswari, and Dhinaharan Nagamalai (Jan 2011)"Web Log Data Analysis and Mining" in Proc CCSIT-2011, Springer CCIS, Vol 133, pp 459-469
  12. White Paper, "Big Data Survey", Gigaspaces, 2012.
  13. http://www. cio. com/slideshow/detail/51062, internet source on 07/05/2014.
  14. W. Fan, & A. Bifet, "Mining Big Data: Current Status, and Forecast to the Future", ACM-SIGKDD Explorations, Vol. 14, Iss. 2, pp. 1-5, 2012.
  15. N. Marz and J. Warren. Big Data: Principles and best practices of scalable realtime data systems. Manning Publications, 2013.
  16. D. Feldman, M. Schmidt, and C. Sohler. Turning big data into tiny data: Constant-size coresets for k-means, pca and projective clustering. In SODA, 2013.
  17. R. Smolan and J. Erwitt, "The Human Face of Big Data", Sterling Publishing Company Incorporated, 2012.
  18. A community white paper developed by leading researchers across the United States "Challenges and Opportunities with Big Data", 2012.
Index Terms

Computer Science
Information Sciences

Keywords

Big Data Big Data Analytics Web Usage Mining.