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Near Neighbor Search in Large Metric Spaces
1995
Very Large Data Bases Conference
Given user data, one often wants to find approximate matches in a large database. A good example of such a task is finding images similar to a given image in a large collection of images. We focus on the important and technically difficult case where each data element is high dimensional, or more generally, is represented by a point in a large metric spaceand distance calculations are computationally expensive. In this paper we introduce a data structure to solve this problem called a GNAT
dblp:conf/vldb/Brin95
fatcat:7ponswfxcja3joojvmqwe6gkjy