Open Access   Article Go Back

An Overview of Data Mining Techniques and its Realtime Applications

K. Chitra Lekha1 , S. Prakasam2

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-12 , Page no. 582-587, Dec-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i12.582587

Online published on Dec 31, 2018

Copyright © K. Chitra Lekha, S. Prakasam . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: K. Chitra Lekha, S. Prakasam, “An Overview of Data Mining Techniques and its Realtime Applications,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.582-587, 2018.

MLA Style Citation: K. Chitra Lekha, S. Prakasam "An Overview of Data Mining Techniques and its Realtime Applications." International Journal of Computer Sciences and Engineering 6.12 (2018): 582-587.

APA Style Citation: K. Chitra Lekha, S. Prakasam, (2018). An Overview of Data Mining Techniques and its Realtime Applications. International Journal of Computer Sciences and Engineering, 6(12), 582-587.

BibTex Style Citation:
@article{Lekha_2018,
author = {K. Chitra Lekha, S. Prakasam},
title = {An Overview of Data Mining Techniques and its Realtime Applications},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {12 2018},
volume = {6},
Issue = {12},
month = {12},
year = {2018},
issn = {2347-2693},
pages = {582-587},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3383},
doi = {https://doi.org/10.26438/ijcse/v6i12.582587}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i12.582587}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3383
TI - An Overview of Data Mining Techniques and its Realtime Applications
T2 - International Journal of Computer Sciences and Engineering
AU - K. Chitra Lekha, S. Prakasam
PY - 2018
DA - 2018/12/31
PB - IJCSE, Indore, INDIA
SP - 582-587
IS - 12
VL - 6
SN - 2347-2693
ER -

VIEWS PDF XML
419 248 downloads 165 downloads
  
  
           

Abstract

Data mining, also prevalently referred as Knowledge innovation from data, is the robotic or expedient withdrawal of patterns representing information implicitly hoard or confined in huge databases, data warehouses, the web, the data streams or other enormous information repositories. Data mining is the expertise that congregates up to the dispute of solving our pursuit for acquaintance from these cosmic data burdens. It affords us with a client oriented loom to novel concealed prototypes in data. This paper accomplishes a prescribed assessment of the perception of data-mining, the typical tasks engross in data-mining, its relevance in day to day field, techniques and methodology. In additional to that, this paper affords insight for concerning the data mining to vindicate the patterns and trends to be utilized suitably and to be a supportive for beginners in the research of data mining. The core intention of this manuscript is to congregate more interior perceptions and skills in data mining.

Key-Words / Index Term

Artificial Intelligence, Time series analysis, Regression, Prediction

References

[1] Kaithekuzhical Leena Kurien and Dr. Ajeet Chikkamannur, ”A Survey on Methodology of Fraud Detection using Data Mining”, International Journal of Trend in Scientific Research and development, Vol.1 ,Issue.6, pp. 38-42, 2017.
[2] D. Ramesh, B. Vishnu Vardhan, “Data Mining Techniques and Applications to Agricultural Yield Data”, International Journal of Advanced Research in Computer and Communication Engineering Vol.2, Issue.9, September 2013.
[3] Fayyad. U, Piatetsky-Shapiro. G., and Smyth. P, ”From Data Mining to Knowledge Discovery: An Overview”, MIT Press, pp.1-36,1996.
[4] H. Benjamin Fredrick David and A. Suruliandi, “Survey on Crime analysis and Prediction using Data mining techniques”, ICTACT Journal on Soft Computing, Vol.7, Issue.3, pp.1459-1466, 2017.
[5] R. Tamilsevi and S. Kalaiselvi, “An Overview of Data Mining Techniques and Applications”, International Journal of Science and Research, Vol.2, Issue.2, pp. 506-509, 2013.
[6] “Data mining tools”, by Ralf Mikut, Markus Reischl, 2011, “Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery”.
[7] Er. Rimmy Chuchra, “Use of Data Mining Techniques for the Evaluation of Student Performance: A Case Study” International Journal of Computer Science and Management Research Vol.1, Issue.3, October 2012.
[8] K. Chitra Lekha and Dr. S. Prakasam, “Data mining Techniques in detecting and predicting Cyber crimes in Banking sector”, IEEE – International Conference on Energy, Communication, Data Analytics and Soft Computing, No. 3, August 2017.
[9] Aakanksha Bhatnagar, Shweta P. Jadye, Madan Mohan Nagar” Data Mining Techniques & Distinct Applications: A Literature Review” International Journal of Engineering Research & Technology (IJERT) Vol.1 Issue 9, November- 2012.
[10] Ruxandra-Ştefania PETRE, “Data mining in Cloud Computing” Database Systems Journal vol. III, no. 3/2012.
[11] K. Chitra Lekha and Dr. S. Prakasam, “Implementation of Data mining techniques for Cyber crime Detection”, International Journal of Engineering, Science and Mathematics, Vol.7, Issue.4, pp. 607-613, 2018.
[12] K.Chitra Lekha and Dr. S. Prakasam, “A Survey on Data Mining Techniques in Cyber Crime”, IEEE –International Conference on Electrical, Electronics, Computers, Communications, Mechanical and Computing, No.2, January 2018.
[13] Mr. S. P. Deshpande and Dr. V. M. Thakare “Data Mining System and Applications: A Review” International Journal of Distributed and Parallel systems, Vol.1, Issue1, September 2010.
[14] Dr. E. Kesavulu Reddy, “Recent Trends in Data mining Techniques”, International Journal of Advance research in Computer Science and Management Studies, Vol.3, Issue.9, pp. 254-262, 2015.
[15] H.-P. Kriegel, K. M. Borgwardt, P. Kröger, A. Pryakhin, M. Schubert, and A. Zimek, “Future trends in data mining,” Data Mining Knowledge Discovery,Vol.15, Issue.1, pp.87-97, 2007.