Email this article An Inverted Index Structure for the Social Image Dataset To Accelerate the Searching Process
Abstract
We suggest a social re-ranking system for tag-based image recovery with the thought of image’s bearing and variety. We purpose at re-ranking images giving to their pictorial information, semantic information and social clues. The original results embrace images underwrote by diverse social users. Regularly each operator underwrites several images. First we type these images by inter-user re-ranking. Users that have higher involvement to the prearranged query rank complex. Then we chronologically instrument intra-user re-ranking on the ranked user’s image set, and first the most appropriate image from each user’s image set is selected. These certain images unite the final retrieved results. We form an inverted index structure for the societal image dataset to fast-track the incisive route.
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