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Content-based image re-ranking technology in search engine
XIE Hui LU Yueming
Journal of Computer Applications
2013, 33 (02):
460-462.
DOI: 10.3724/SP.J.1087.2013.00460
As the existing text-based image search results sorting cannot meet the users' query expectations, two kinds of content-based re-ranking methods for image search results named SI (Similarity Integral) algorithm and D (Dijkstra) algorithm were put forward. These methods treated images as nodes, used the color and shape features to calculate the similarity between images, and took the similarity as the edge's weight to construct the similarity graph. SI algorithm sorted the images according to the similarity integral of each node image, and D algorithm traversed all the images from the specified image by Dijkstra algorithm. The experimental results show that both of the methods can improve the sorting performance of the image search. In addition, SI algorithm is suitable for the situation with initial precision rate at 0.5-0.9, while D algorithm does not require the initial precision rate, but has high accuracy requirements of similarity value between images, and can be used to the images re-ranking queried by an specified image.
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