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In this paper, the authors focus on the problem of shape retrieval and clustering. They put two questions together because they are based on the same method, called Improved Graph Transduction. For shape retrieval, they regard the shape as a node in a graph and the similarity of shapes is represented by the edge of the graph. Then they learn a new distance measure between the query shape and the testing shapes. The main contribution of their work is to merge the most likely node with the query node during the learning process.
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