An approach for cross-media retrieval with cross-reference graph and PageRank
An approach for cross-media retrieval with cross-reference graph and PageRank
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DOI：
10.1109/mmmc.2006.1651316
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发表时间：
2006-07
期刊：
影响因子：
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通讯作者：
Yueting Zhuang;Hanhuai Shan;Fei Wu
中科院分区：
文献类型：
--
作者：
Yueting Zhuang;Hanhuai Shan;Fei Wu
本文提出了一种新的跨媒体检索方法。该方法最重要的特点是通过交叉引用图将多模态数据无缝集成，然后基于交叉引用图，利用改进的个性化PageRank计算媒体对象与查询在语义和内容层面的关联程度。并能根据用户的相关性反馈调整交叉参考图，细化媒体对象之间的语义关系，从而逐步提高检索精度。实验结果表明，该方法在多模态数据集上取得了令人满意的检索效率
In this paper, we propose a novel cross-media retrieval method. The most important feature of it is to integrate the multi-modal data seamlessly via a cross-reference graph, and then based on the graph, it is able to use improved personalized PageRank to calculate how close the media object associates with the query on semantic and content level. It is also able to adjust the cross-reference graph according to user's relevance feedback, which refines the semantic relationship between the media objects, so as to improve the retrieval accuracy progressively. As demonstrated by the experiments, our method achieves satisfactory retrieval efficiency on multi-modal datasets