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Research Article Open Access
Web-scale image search engines often uses keywords as queries and also depends on neighbouring text to search images. These search engines entails difficulty due to the ambiguity of query keywords, since it is hard for users to correctly depict the visual content of target images by only using keywords. Image re-ranking is an efficient way to advance the results of web-based image search, has been implemented by commercial search engines such as Google and Bing. A main challenge in the research of image re-ranking is that the similarities of visual features do not well associate with semantic meanings of images which infer users’ search goal. This paper surveys various methods which developed recently used for image re-ranking techniques for different queries. Each method is differentiated with other surveyed method and comparative measures of methods are presented which provides the significance and limitations of web image re-ranking techniques with correspond to query specific semantic signatures.