ABSTRACT
In this article, we give an overview of efficient algorithms for the approximate and exact nearest neighbor problem. The goal is to preprocess a dataset of objects (e.g., images) so that later, given a new query object, one can quickly return the dataset object that is most similar to the query. The problem is of significant interest in a wide variety of areas.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
 |
1
|
|
| |
2
|
Andoni, A. and Indyk, P. 2004. E2lsh: Exact Euclidean localitysensitive hashing. http://web.mit.edu/andoni/www/LSH/.
|
| |
3
|
|
 |
4
|
|
| |
5
|
Sunil Arya , David M. Mount , Nathan S. Netanyahu , Ruth Silverman , Angela Wu, An optimal algorithm for approximate nearest neighbor searching, Proceedings of the fifth annual ACM-SIAM symposium on Discrete algorithms, p.573-582, January 23-25, 1994, Arlington, Virginia, United States
|
 |
6
|
|
| |
7
|
|
| |
8
|
Andrei Z. Broder , Steven C. Glassman , Mark S. Manasse , Geoffrey Zweig, Syntactic clustering of the Web, Selected papers from the sixth international conference on World Wide Web, p.1157-1166, September 1997, Santa Clara, California, United States
|
| |
9
|
|
| |
10
|
Buhler, J. 2001. Efficient large-scale sequence comparison by locality-sensitive hashing. Bioinform. 17, 419--428.
|
 |
11
|
|
| |
12
|
Califano, A. and Rigoutsos, I. 1993. Flash: A fast look-up algorithm for string homology. In Proceedings of the IEE Conference on Computer Vision and Pattern Recognition (CVPR).
|
| |
13
|
|
 |
14
|
|
| |
15
|
|
| |
16
|
Cormen, T. H., Leiserson, C. E., Rivest, R. L., and Stein, C. 2001. Introduct. Algorithms. 2nd Ed. MIT Press.
|
 |
17
|
Mayur Datar , Nicole Immorlica , Piotr Indyk , Vahab S. Mirrokni, Locality-sensitive hashing scheme based on p-stable distributions, Proceedings of the twentieth annual symposium on Computational geometry, June 08-11, 2004, Brooklyn, New York, USA
[doi> 10.1145/997817.997857]
|
| |
18
|
Dutta, D., Guha, R., Jurs, C., and Chen, T. 2006. Scalable partitioning and exploration of chemical spaces using geometric hashing. J. Chem. Inf. Model. 46.
|
| |
19
|
|
 |
20
|
|
| |
21
|
Greene, D., Parnas, M., and Yao, F. 1994. Multi-index hashing for information retrieval. In Proceedings of the Symposium on Foundations of Computer Science. 722--731.
|
| |
22
|
|
| |
23
|
Haveliwala, T., Gionis, A., and Indyk, P. 2000. Scalable techniques for clustering the web. WebDB Workshop.
|
| |
24
|
Indyk, P. 2003. Nearest neighbors in high-dimensional spaces. In Handbook of Discrete and Computational Geometry. CRC Press.
|
 |
25
|
|
| |
26
|
|
 |
27
|
|
| |
28
|
|
 |
29
|
Eyal Kushilevitz , Rafail Ostrovsky , Yuval Rabani, Efficient search for approximate nearest neighbor in high dimensional spaces, Proceedings of the thirtieth annual ACM symposium on Theory of computing, p.614-623, May 24-26, 1998, Dallas, Texas, United States
[doi> 10.1145/276698.276877]
|
| |
30
|
Linial, N., London, E., and Rabinovich, Y. 1994. The geometry of graphs and some of its algorithmic applications. In Proceedings of the Symposium on Foundations of Computer Science. 577--591.
|
 |
31
|
|
 |
32
|
|
| |
33
|
|
| |
34
|
|
| |
35
|
|
| |
36
|
|
| |
37
|
Terasawa, T. and Tanaka, Y. 2007. Spherical lsh for approximate nearest neighbor search on unit hypersphere. In Proceedings of the Workshop on Algorithms and Data Structures.
|
CITED BY 4
|
|
|
|
|
|
|
|
|
|
|
Andreas Sæbjørnsen , Jeremiah Willcock , Thomas Panas , Daniel Quinlan , Zhendong Su, Detecting code clones in binary executables, Proceedings of the eighteenth international symposium on Software testing and analysis, July 19-23, 2009, Chicago, IL, USA
|
|