• Akshay Rajendra Sav
• Prof. M.B. Vaidya

Social media sharing websites like Flickr allow users to annotate images with free tags, which significantly contribute to the development of the web image retrieval and organization. Tag-based image search is an important method to find images contributed by social users in such social websites. However, how to make the top ranked result relevant and with diversity is challenging. In this paper, we propose a social re-ranking system for tag-based image retrieval with the consideration of images relevance and diversity. We aim at re-ranking images according to their visual information, semantic information and social clues. The initial results include images contributed by different social users. Usually each user contributes several images. First we sort these images by inter-user re-ranking. Users that have higher contribution to the given query rank higher. Then we sequentially implement intra-user re-ranking on the ranked users image set, and only the most relevant image from each users image set is selected. These selected images compose the final retrieved results. We build an inverted index structure for the social image dataset to accelerate the searching process.

Social Media, Tag-based Image Retrieval, Social Clues, Image search, Re-ranking

"Multi-Attribute Tag Based Image Search By Social Re-Ranking", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.864-867, June-2019, Available :http://www.jetir.org/papers/JETIR1906418.pdf

"Multi-Attribute Tag Based Image Search By Social Re-Ranking", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp864-867, June-2019, Available at : http://www.jetir.org/papers/JETIR1906418.pdf