IRAbMC : Image Recommendation with Absorbing Markov Chain

Sejal, D and Rashmi, V and Anvekar, Dinesh and Venugopal, KR and Iyengar, SS and Patnaik, LM (2015) IRAbMC : Image Recommendation with Absorbing Markov Chain. In: 12 IEEE Int C Elect Energy Env Communications Computer Control, DEC 17-20, 2015, New Delhi, INDIA.

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Abstract

Image Recommendation is an important feature for search engine as tremendous amount images are available online. It is necessary to retrieve relevant images to meet user's requirement. In this paper, we present an algorithm Image Recommendation with Absorbing Markov Chain ( JRAbMC) to retrieve relevant images for user input query. Images are ranked by calculating keyword relevance probability between annotated keywords from log and keywords of user input query. Absorbing Markov chain is used to calculate keyword relevance. Experiments results show that the JRAbMC algorithm outperforms Markovian Semantic Indexing (MSI) method with improved relevance score of retrieved ranked images.

Item Type:	Conference Proceedings
Series.:	Annual IEEE India Conference
Additional Information:	Copy right for this article belongs to the IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Department/Centre:	Division of Electrical Sciences > Electronic Systems Engineering (Formerly Centre for Electronic Design & Technology)
Date Deposited:	06 Dec 2016 10:31
Last Modified:	06 Dec 2016 10:31
URI:	http://eprints.iisc.ac.in/id/eprint/54745

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