DOI:10.20894/IJDMTA.
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 admin@iirgroups.org

Paper Template
Copyright Form
Subscription Form
web counter
web counter
Published in:   Vol. 4 Issue 2 Date of Publication:   December 2015

Effective Approaches of Classification Algorithms for Text Mining Applications

U.Latha,T.Velmurugan

Page(s):   103-107 ISSN:   2278-2397
DOI:   10.20894/IJDMTA.102.004.002.012 Publisher:   Integrated Intelligent Research (IIR)

The large amount of data stored in unstructured texts cannot simply be used for further processing by computers, which typically handle text as simple sequences of character strings. Therefore, specific (pre-) processing methods and algorithms are required in order to retrieve useful information via text. Text mining refers generally to the process of retrieving information and knowledge from formless text. This research work analyses about the use of classification algorithms and their uses to predict the applications of text mining. The purpose of this work is to present an analysis of recent publications concerning with text mining using classification algorithm in particular. This survey finds out some of the best suitable algorithms for text mining analyses suggested by the various researchers in their research work.