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	Effective Heterogeneous Similarity Measure with Nearest Neighbors for Cross-Media Retrieval
	Zhai, Xiaohua ; Peng, Yuxin ; Xiao, Jianguo
	2012
关键词	cross-media cross-modal multimedia retrieval heterogeneous similarity measure QUERY
英文摘要	Emerging multimedia content including images and texts are always jointly utilized to describe the same semantics. As a result, cross-media retrieval becomes increasingly important, which is able to retrieve the results of the same semantics with the query but with different media types. In this paper, we propose a novel heterogeneous similarity measure with nearest neighbors (HSNN). Unlike traditional similarity measures which are limited in homogeneous feature space, HSNN could compute the similarity between media objects with different media types. The heterogeneous similarity is obtained by computing the probability for two media objects belonging to the same semantic category. The probability is achieved by analyzing the homogeneous nearest neighbors of each media object. HSNN is flexible so that any traditional similarity measure could be incorporated, which is further regarded as the weak ranker. An effective ranking model is learned from multiple weak rankers through AdaRank for cross-media retrieval. Experiments on the wikipedia dataset show the effectiveness of the proposed approach, compared with state-of-the-art methods. The cross-media retrieval also shows to outperform image retrieval systems on a unimedia retrieval task.; http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000306579900030&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701 ; Computer Science, Hardware & Architecture; Computer Science, Theory & Methods; EI; CPCI-S(ISTP); 2
语种	英语
DOI标识	10.1007/978-3-642-27355-1_30
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/321216]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Zhai, Xiaohua,Peng, Yuxin,Xiao, Jianguo. Effective Heterogeneous Similarity Measure with Nearest Neighbors for Cross-Media Retrieval. 2012-01-01.

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