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首页> 外文期刊>Pattern Recognition: The Journal of the Pattern Recognition Society >Hypergraph-based image retrieval for graph-based representation
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Hypergraph-based image retrieval for graph-based representation

机译:基于超图的图像检索,用于基于图的表示

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摘要

In this paper, we introduce a novel method for graph indexing. We propose a hypergraph-based model for graph data sets by allowing cluster overlapping. More precisely, in this representation one graph can be assigned to more than one cluster. Using the concept of the graph median and a given threshold, the proposed algorithm detects automatically the number of classes in the graph database. We consider clusters as hyperedges in our hypergraph model and we index the graph set by the hyperedge centroids. This model is interesting to traverse the data set and efficient to retrieve graphs.
机译:在本文中,我们介绍了一种新颖的图形索引方法。通过允许集群重叠,我们为图形数据集提出了一个基于超图的模型。更精确地,在该表示中,可以将一个图分配给一个以上的群集。利用图中位数和给定阈值的概念,所提出的算法自动检测图数据库中的类数。在我们的超图模型中,我们将聚类视为超边,并通过超边形质心对图集进行索引。该模型对于遍历数据集很有趣,并且对于检索图形很有效。

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