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With the increasing number of Web images and social photograph sharing sites, effective search of real-world images becomes a formidable challenge and an important necessity. Different indexing and annotation algorithms are required for different types of Web images. To meet the challenge and provide satisfactory search results to users, we present a multi-level method with four levels differentially applied to different types of Web images. The performance of our method is evaluated by experiments on thousands of Web images and tags in different subsets, and our approach is able to yield highly promising results compared with applying a single method to all types of Web images

Multi-Level Semantic Characterization and Refinement for Web Image Search