Periodicity: Bi Annual.
Impact Factor:
SJIF:4.893 & GIF:0.787
Submission:Any Time
Publisher: IIR Groups
Language: English
Review Process:
Double Blinded

News and Updates

Author can submit their paper through online submission. Click here

Paper Submission -> Blind Peer Review Process -> Acceptance -> Publication.

On an average time is 3 to 5 days from submission to first decision of manuscripts.

Double blind review and Plagiarism report ensure the originality

IJDMTA provides online manuscript tracking system.

Every issue of Journal of IJDMTA is available online from volume 1 issue 1 to the latest published issue with month and year.

Paper Submission:
Any Time
Review process:
One to Two week
Journal Publication:
June / December

IJDMTA special issue invites the papers from the NATIONAL CONFERENCE, INTERNATIONAL CONFERENCE, SEMINAR conducted by colleges, university, etc. The Group of paper will accept with some concession and will publish in IJDMTA website. For complete procedure, contact us at

Paper Template
Copyright Form
Subscription Form
web counter
web counter
Published in:   Vol. 3 Issue 1 Date of Publication:   June 2014

A Novel Approach to Mathematical Concepts in Data Mining

I.Benjamin Franklin,V.Julian Arockiaraj

Page(s):   38-41 ISSN:   2278-2397
DOI:   10.20894/IJDMTA. Publisher:   Integrated Intelligent Research (IIR)

This paper describes three different fundamental mathematical programming approaches that are relevant to data mining. They are: Feature Selection, Clustering and Robust Representation. This paper comprises of two clustering algorithms such as K-mean algorithm and K-median algorithms. Clustering is illustrated by the unsupervised learning of patterns and clusters that may exist in a given databases and useful tool for Knowledge Discovery in Database (KDD). The results of k-median algorithm are used to collecting the blood cancer patient from a medical database. K-mean clustering is a data mining/machine learning algorithm used to cluster observations into groups of related observations without any prior knowledge of those relationships. The kmean algorithm is one of the simplest clustering techniques and it is commonly used in medical imaging, biometrics and related fields.