DOI:10.20894/IJCOA.
Periodicity: Bi Annual.
Impact Factor:
SJIF:5.079 & GIF:0.416
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

IJCOA provides online manuscript tracking system.

Every issue of Journal of IJCOA 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

IJCOA 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 IJCOA 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 1 Date of Publication:   June 2015

An Emphasized Dual Similarity Measure Integration for Online Image Retrieval System Using SimRank

R.RajKumar,M.Krishnamurthy

Page(s):   1-5 ISSN:   2278-2397
DOI:   10.20894/IJCOA.101.004.001.001 Publisher:   Integrated Intelligent Research (IIR)

In the real world scenario the use of image grows rapidly, the image rich network is the one that comprises of billions of images. The social media websites, such as Picasa, Flickr and Facebook comprises billions of end user posted images along with their annotations. Similarly the electronic commerce website such as Flipkart, Myntra and Amazon are also furnished with product related images. In this paper, we introduce how to perform efficient and optimum information retrieval in online image rich system. We propose a Mok-SimRank to compute link-based similarity and a dual similarity integration algorithm for both link and content based similarity. Experimental results on online electronic commerce site show that our approach is significantly better than traditional methods in terms of relevance.