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Reseach Article

A Survey on Data Mining Approaches

by Amirmahdi Mohammadighavam, Neda Rajabpour, Ali Naserasadi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 36 - Number 6
Year of Publication: 2011
Authors: Amirmahdi Mohammadighavam, Neda Rajabpour, Ali Naserasadi
10.5120/4495-6338

Amirmahdi Mohammadighavam, Neda Rajabpour, Ali Naserasadi . A Survey on Data Mining Approaches. International Journal of Computer Applications. 36, 6 ( December 2011), 14-18. DOI=10.5120/4495-6338

@article{ 10.5120/4495-6338,
author = { Amirmahdi Mohammadighavam, Neda Rajabpour, Ali Naserasadi },
title = { A Survey on Data Mining Approaches },
journal = { International Journal of Computer Applications },
issue_date = { December 2011 },
volume = { 36 },
number = { 6 },
month = { December },
year = { 2011 },
issn = { 0975-8887 },
pages = { 14-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume36/number6/4495-6338/ },
doi = { 10.5120/4495-6338 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:23:06.809640+05:30
%A Amirmahdi Mohammadighavam
%A Neda Rajabpour
%A Ali Naserasadi
%T A Survey on Data Mining Approaches
%J International Journal of Computer Applications
%@ 0975-8887
%V 36
%N 6
%P 14-18
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In the new world, with advances in modern industries and businesses and increase in the growing need for data with reference to the knowledge of data processing in order to participate in a big competitive market, led all to the new techniques for mass processing of raw data on their role in data mining due to the direct use of the machine And thereby increase the speed, accuracy and quality of information is much more important than other methods. Hence in this paper the concept and meaning of the data mining techniques and models used in data mining and data mining is the major subtype web mining has been studied. Finally, we have examined and reviewed the latest achievements in data mining and new approaches that have covered.

References
  1. ZhaoHui Tang, Jamie MacLennan, “Data mining with SQLSERVER2005”.
  2. Hamid R. Nemati and Charmion Brathwait , Kara Harrington , “Privacy Implications of Organizational Data Mining” , 2004.
  3. Jiawei Han & Micheline Kamber, “Data Mining Concept and Techniques”, 2000.
  4. DANIEL T.LAROSE, WILEY INTERSCIENCE, "Discovery Knowledge in Data, An Introduction to Data Mining.
  5. David M. & Natalie M. Stiger, Stiger University of Maine, USA "Knowledge Mining in DSS Model Analysis", 2004.
  6. Hamid R. Nemati and Christopher D.Barko – University Of North Carolina at Greensboro, USA 2004"Oraganizational Data Mining (ODM): An Introduction" (Springer).
  7. Michael J.A Berry, Gordan S. Linoff Wiley - "Data Mining Techniques for Marketing Sales and Customer Support Management.
  8. Two Crows Corporation, Introduction to Data Mining and Knowledge Discovery, 1999.
  9. Web Mining Research, Raymond Kosala, Hendrik Blockeel.
  10. Web Mining, Accomplishments & Future Directions, Jaideep Srivastava University of Minnesota, USA.
  11. THE HAND BOOK OF DATA MINING, ARIZONA STATE UNIVERSITY, 2003.
  12. Application of Cluster-Based Local Outlier Factor Algorithm in Anti-Money Laundering, School of Economics and Management Southwest Jiaotong University, Gao Zengan.
  13. Detecting Money Laundering and Terrorist Financing via Data Mining, John S. Zdanowicz.
  14. Intelligent Miner for Data, Joerg Reinschmidt, Helena Gottschalk, Hosung Kim, Damiaan Zwietering.
  15. Data Mining in Earth System Science (DMESS 2011), International Conference on Computational Science, ICCS 2011, Forrest M. Hoffman, J. Walter Larson, Richard Tran Mills.
  16. D. Cook, J. Hartnett, K. Manderson and J. Scanlan, Catching Spam before it Arrives.
  17. Pfleeger, SL & Bloom, “Canning Spam: Proposed Solutions to Unwanted Email”, Security & Privacy Magazine, IEEE.
  18. Airoldi, E, Malin, B. “Data mining challenges for electronic safety.
  19. Nm Y. Yang, An evaluation of statistical approaches to text categorization.
  20. N. Littlestone and M. Warmuth , “Weighted majority algorithm.
Index Terms

Computer Science
Information Sciences

Keywords

Data Mining Web Mining Text Mining Mass Processing Machine Processing