Cover trees for nearest neighbor
IBM Research - Thomas J. Watson Research Center · IBM (United States) · +1 more institution
Abstract
We present a tree data structure for fast nearest neighbor operations in general n-point metric spaces (where the data set consists of n points). The data structure requires O(n) space regardless of the metric's structure yet maintains all performance properties of a navigating net (Krauthgamer & Lee, 2004b). If the point set has a bounded expansion constant c, which is a measure of the intrinsic dimensionality, as defined in (Karger & Ruhl, 2002), the cover tree data structure can be constructed in O (c6n log n) time. Furthermore, nearest neighbor queries require time only logarithmic in n, in particular O (c12 log n) time. Our experimental results show speedups over the brute force search varying between one…
Citation impact
- FWCI
- 31.62
- Percentile
- 100%
- References
- 18
Authors
3Topics & keywords
- Cover tree
- k-nearest neighbors algorithm
- Curse of dimensionality
- Nearest neighbor search
- Metric (unit)
- Cover (algebra)
- Metric space
- Logarithm