Computer Sciences


Data Mining Techniques: A Study

Article Number: EVM599070 Volume 01 | Issue 01 | January - 2019 ISSN: UA
19th Sep, 2018
20th Oct, 2018
26th Dec, 2018
07th Jan, 2019

Authors

Devendra Sharma, Aman Sharma

Abstract

Data mining is the extraction of relevant details, patterns and trends from heavy data. Data mining involves techniques such as clustering, classification, association and regression. There are various applications of data mining that uses various tools that supports different algorithms. This paper provides various data mining techniques and can also applied in the educational sector, marketing, detection of frauds, the telecommunication and manufacturing. As data mining is the notion of all methods and techniques that allows the analysis of large set of data to extract and discover unknown structures and their relations out of large details. Keywords: data mining techniques, Fraud detection, Clustering

Introduction

Data mining extraction and mining of the significant or relevant data from large amount of data and it is also known as “Knowledge mining”. The technology for storing and collection of data has made the accumulation of large amounts of data affordable. This stored data is exploited for making the extraction useful and information should be actionable which is considered as the goal of the generic activity that is referred to as data mining.

This discipline is a field of computer science that basically involves the computational (digital) process of data sets in large quantity and then transform it into a structure that should be understandable for further usage (Jain and Srivastava, 2013).

The Information Development Technology has produced databases in large amount in various areas or regions. The database and information technology research has opened doors to some approaches that stores and manipulates the previously existed data for the decision making process. 

References

A, Parkavi, et al. “Predicting Effective Course Conduction Strategy Using Datamining Techniques.” Academic Journals, vol. 12, no. 24, Dec. 2017, pp. 1188–1198.

Dogra, Ashish Kumar, and Tanuj Wala. “A Review Paper on Data Mining Techniques and Algorithms.” International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), vol. 4, no. 5, May 2015, pp. 1976–1979.

Gera, Mansi, and Shivani Goel. “Data Mining - Techniques, Methods and Algorithms: A Review on Tools and Their Validity.” International Journal of Computer Applications, vol. 113, ser. 18, Mar. 2015, pp. 22–29. 18.

Gulati, Pooja, and Archana Sharma. “Educational Data Mining for Improving Educational Quality.” IRACST - International Journal of Computer Science and Information Technology & Security (IJCSITS, vol. 2, ser. 3, June 2012, pp. 648–650. 3.

Hilage, Tejaswini Abhijit, and R V Kulkarni. “Application of Data Mining Techniques to a Selected Business Organization with Special Reference to Buying Behavior.” International Journal of Database Management Systems (IJDMS), vol. 3, ser. 4, Nov. 2011, pp. 169–181. 4.

Jain, Nikita, and Vishal Srivastava. “DATA MINING TECHNIQUES: A SURVEY PAPER.” IJRET: International Journal of Research in Engineering and Technology, vol. 2, no. 11, Nov. 2013, pp. 116–119.

Mohata, Pranit B, and Sheetal Dhande. “Web Data Mining Techniques and Implementation for Handling Big Data.” International Journal of Computer Science and Mobile Computing, vol. 4, no. 4, Apr. 2015, pp. 330–334.

Ramageri, Bharati M. “DATA MINING TECHNIQUES AND APPLICATIONS.” Indian Journal of Computer Science and Engineering, vol. 1, no. 4, pp. 301–305.

Silwattananusarn, Tipawan, and Kulthida Tuamsuk. “Data Mining and Its Applications for Knowledge Management: A Literature Review from 2007 to 2012.” International Journal of Data Mining & Knowledge Management Process, vol. 2, no. 5, 2012, pp. 13–24., doi:10.5121/ijdkp.2012.2502.

Smita, and Priti Sharma. “Use of Data Mining in Various Field: A Survey Paper.” IOSR Journal of Computer Engineering (IOSR-JCE), vol. 16, no. 3, 2014, pp. 18–21.

How to cite this article?

APA StyleSharma, D., & Sharma, A. (2019). Data Mining Techniques: A Study. Academic Journal of Computer Sciences, 1(1), 13-17.
Chicago Style
MLA Style
DOI
URL

Create Your Password

We've sent a link to create password on your registered email, Click the link in email to start using Xournal.

Sign In

Forgot Password?
Don't have an account? Create Account

Create Account

Already have an account? Sign In

Forgot Password

Do you want to try again? Sign In

Publication Tracking