Data structures and algorithms for nearest neighbor search in general metric spaces
Peter N. Yianilos
- pp 311-321
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TLDR
The up-tree (vantage point tree) is introduced in several forms, together‘ with &&ciated algorithms, as an improved method for these difficult search problems in general metric spaces.Abstract:
We consider the computational problem of finding nearest neighbors in general metric spaces. Of particular interest are spaces that may not be conveniently embedded or approximated in Euclidian space, or where the dimensionality of a Euclidian representation 1s very high. Also relevant are high-dimensional Euclidian settings in which the distribution of data is in some sense of lower dimension and embedded in the space. The up-tree (vantage point tree) is introduced in several forms, together‘ with &&ciated algorithms, as an improved method for these difficult search nroblems. Tree construcI tion executes in O(nlog(n i ) time, and search is under certain circumstances and in the imit, O(log(n)) expected time. The theoretical basis for this approach is developed and the results of several experiments are reported. In Euclidian cases, kd-tree performance is compared.read more
Citations
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An 86 mW 98GOPS ANN-Searching Processor for Full-HD 30 fps Video Object Recognition With Zeroless Locality-Sensitive Hashing
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Lower Bounds on Performance of Metric Tree Indexing Schemes for Exact Similarity Search in High Dimensions
TL;DR: In this paper, the authors analyzed the curse of dimensionality for deterministic exact similarity search in the context of popular indexing schemes, such as metric trees, and deduced the Ω(n 1/4) lower bound on the expected average case performance of hierarchical metric tree based indexing.
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Beyond Near Duplicates: Learning Hash Codes for Efficient Similar-Image Retrieval
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DBM-Tree: trading height-balancing for performance in metric access methods
TL;DR: A new dynamic MAM called the DBM-tree (Density-Based Metric tree), which can minimize the overlap between high-density nodes by relaxing the height-balancing of the structure, and an optimization algorithm called Shrink is presented, which improves the performance of an already builtDBM-tree by reorganizing the elements among their nodes.
Patent
Image searching by approximate κ-NN graph
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References
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