Active Congruency-Based Reranking

Itai Ben-Shalom, Noga Levy, Lior Wolf, N. Dershowitz, Adiel Ben-Shalom, Roni Shweka, Y. Choueka, Tamir Hazan, Yaniv Bar
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引用次数: 0

Abstract

We present a tool for re-ranking the results of a specific query by considering the matrix of pairwise similarities among the elements of the set of retrieved results and the query itself. The re-ranking thus makes use of the similarities between the various results and does not employ additional sources of information. The tool is based on graphical Bayesian models, which reinforce retrieved items strongly linked to other retrievals, and on repeated clustering to measure the stability of the obtained associations. To this, we add an active relevance-based re-ranking process in order to leverage true matches, which have very low similarity to the query. The utility of the tool is demonstrated within the context of a visual search of documents from the Cairo Genizah. It is also demonstrated in a completely different domain or retrieving, given an input image of a painting, other related paintings.
基于主动一致性的重排序
我们提出了一种工具,通过考虑检索结果集和查询本身元素之间的成对相似性矩阵,对特定查询的结果进行重新排序。因此,重新排序利用了各种结果之间的相似性,而不使用额外的信息来源。该工具基于图形贝叶斯模型,该模型强化了与其他检索强烈相关的检索项目,并通过重复聚类来测量获得的关联的稳定性。为此,我们添加了一个主动的基于相关性的重新排序过程,以利用与查询相似度非常低的真实匹配。在Cairo Genizah文档的可视化搜索上下文中演示了该工具的实用程序。它也被展示在一个完全不同的领域或检索中,给定一幅画的输入图像,其他相关的画。
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