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A cost model for nearest neighbor search in high-dimensional data space
Open accessAbstract
In this paper, we present a new cost model for nearest neighbor search in high-dimensional data space. We first analyze different nearest neighbor algorithms, present a generalization of an algorithm which has been originally proposed for Quadtrees [13], and show that this algorithm is optimal. Then, we develop a cost model which- in contrast to previous models- takes boundary effects into account and therefore also works in high dimensions. The advantages of our model are in particular: Our model works for data sets with an arbitrary number of dimensions and an arbitrary number of data points, is applicable to different data distributions and index structures, and provides accurate estimates of the expected query execution time. To show the practical relevance and accuracy of our model, we perform a detailed analysis using synthetic and real data. The results of applying our model to
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Cited by
When Is ''Nearest Neighbor'' Meaningful?
Beyer, K., Goldstein, J., Ramakrishnan, R., & Shaft, U. (1999) · Lecture Notes in Computer Science · doi:10.1007/3-540-49257-7_15 · Cited by 2,403
Automatic subspace clustering of high dimensional data for data mining applications
Agrawal, R., Gehrke, J., Gunopulos, D., & Raghavan, P. (1998) · Proceedings of the 1998 ACM SIGMOD international conference on Management of data · doi:10.1145/276304.276314 · Cited by 2,412
A survey on unsupervised outlier detection in high‐dimensional numerical data
Zimek, A., Schubert, E., & Kriegel, H. (2012) · Statistical Analysis and Data Mining The ASA Data Science Journal · doi:10.1002/sam.11161 · Cited by 864
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Metadata
- Authors
- Berchtold, S., Böhm, C., Keim, D. A., & Kriegel, H.-P.
- Venue
- Proceedings of the sixteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
- Publisher
- ACM
- Published
- 1997-05
- Pages
- 78-86
- OpenAlex
- W2104128006
- Cited by
- 373
- References
- 0
- FWCI
- 40.49
- Type
- conference paper
- Language
- en
- Open access
- green
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- CoChat. (2026). Citation check: A cost model for nearest neighbor search in high-dimensional data space. https://app.cochat.ai/papers/10.1145/263661.263671
- The paper
- Berchtold, S., Böhm, C., Keim, D. A., & Kriegel, H.-P. (1997). A cost model for nearest neighbor search in high-dimensional data space. Proceedings of the sixteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems. https://doi.org/10.1145/263661.263671
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