A SURVEY ON WEB IMAGE SEARCH RE-RANKING WITH CLICK BASED SIMILARITY

IT Skills Show & International Conference on Advancements in Computing Resources, (SSICACR-2017) 15 and 16 February 2017, Alagappa University, Karaikudi, Tamil Nadu, India. International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)

Abstract

Image processing is a technique to retrieve the images stored b various social Networks. The Existing methods used to mine the accurate images are not feasible one. This paper proposed a method to fulfill the Semantic Gap and Intent gap which is the gap between the user’s query and retrieved images. To overcome the intent gap, Image click through data can be viewed as the feedback from users in order to improve search performance. This paper proposes a novel reranking approach, named spectral clustering reranking with click based similarity and typicality. To estimate the similarity measurement, Click based multi feature learning algorith are used. Then based on the results obtained from the learning algorithm, final rerank list are created by the typicality measurement. Thus the proposed algorithm outperforms the existing one in terms of complexity and accuracy.

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