References
- A. Andoni and P. Indyk, "Near-optimal Hashing Algorithms for Approximate Nearest Neighbor in High Dimensions," Comm. ACM, vol.51, no.1, pp.117-122, 2008. https://doi.org/10.1145/1327452.1327494
- S. Baluja and M. Covell, "Learning Forgiving Hash Functions: Algorithms and Large Scale Tests," Proc. 20th Int. Joint Conf. on Artifical intelligence, pp. 2663-2669, 2007.
- J. L. Bentley, "Multidimensional Binary Search Trees used for Associative Searching," Commun. Ass. Comput. Mach., vol. 19, pp. 509-517, 1975.
- S. Boriah, V. Chandola, and V. Kumar, "Similarity Measures for Categorical Data: A Comparative Evaluation," Proc. of the 8th SIAM Int. Conf. on Data Mining, pp.243-254, 2008.
- A. Z. Broder, "On the Resemblance and Containment of Documents," Proc. Compression and Complexity of Sequence, pp. 21-29, 1997.
- A. Z. Broder, M. Charikar, A. M. Frieze, and M. Mitzenmacher, "Min-wise Independent Permutations," ACM Symposium on Theory of Computing, pp. 327-336, 1998.
- M. Datar, N. Immorlica, P. Indyk, and V. S. Mirrokni, "Locality-sensitive Hashing Scheme based on p-stable Distribution," Symp. on Computational Geometry, pp. 253-262, 2004.
- D. G. Lowe, "Object recognition from local scaleinvariant features," Proc. of the Int.l Conf. on Computer Vision, vol.2. pp.1150-1157, 1999.
- A. Gionis, P. Indyk, and R. Motwani, "Similarity Search in High Dimensions via Hashing," Proc. of VLDB, 1999.
- Y. Gong, S. Lazebnik, A. Gordo, and F. Perronnin, "Iterative quantization: A Procrustean approach to learning binary codes for large-scale image retrieval," IEEE Trans. Pattern Anal. Mach. Intell., 2012.
- A. Guttman, "R-Trees: A Dynamic Index Structure for Spatial Searching," Proc. of SIGMOD'84, 1984.
- J. Hays and A. A. Efros, "Scene Completion Using Millions of Photographs," Proc. of SIGGRAPH, 2007.
- J. He, W. Liu, and S.-F. Chang, "Scalable Similarity Search with Optimized Kernel Hashing," Proc. of IEEE Int. Conf. on Knowledge Discovery and Data Mining, pp.1129-1138 2010.
- H. Henzinger, "Finding Nearest-Duplicate Web Pages: a Large-Scale Evaluation of Algorithms," Proc. of SIGIR, pp. 284-291, 2006.
- J.-P. Heo, Y. Lee, J. He, S.-F. Chang, and S.-E. Yoon, "Spectral Hashing," Proc. of CVPR, 2012.
- P. Indyk and R. Motwani, "Approximate Nearest Neighbors: Towards Removing the Curse of Dimensionality," Proc. of STOC, 1998.
- Q. Jiang and M. Sun, "Semi-supervised Simhash for Efficient Document Similarity Search," Proc. The 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, pp.93-101, 2011.
- W. Kong and W.-J. Li, "Isotropic Hashing," Proc. of NIPS2012, 2012.
- W. Kong, W.-J. Li, and M. Guo, "Manhattan hashing for large-scale image retrieval," Proc. of SIGIR, 2012.
- Y. Koren, "Factorization Meets the Neighborhood: a Multifaceted Collaborative Filtering Model," KDD, 2008.
- A. Krizhevsky, V. Nair, and G. Hinton, The CIFAR-10 and CIFAR-100 Databases, http://www.cs.toronto.edu/ kriz/cifar.html.
- B. Kulis and K. Grauman, "Kernelized Localitysensitive Hashing," Proc. of 12th Int. Conf. on Computer Vision, 2009.
- B. Kulis and T. Barrell, "Learning to Hash with Binary Reconstructive Embeddings," Tech. Rep., UC Berkeley, 2009.
- B. Kulis, P. Jain, and K. Grauman, "Fast Similarity Search for Learned Metrics," IEEE TPAMI, vol.31, no. 12, 2009.
- Y. LeCun and C. Cortes, MNIST Database, http://yann. lecun.com/exdb/mnist/.
- K. M. Lee and K.M. Lee, "A Locality Sensitive Hashing Technique for Categorical Data," Applied Mech. And Mat., 2013(to appear).
- F.-F. Li, M. Andreetto, and M. A. Ranzato, Caltech 101 Database, http://www.vision.caltech.edu/ImageDatasets/Caltech101/.
- Y. Lin, D. Cai, "Density Sensitive Hashing," ArXive-prints arXiv:1205.2930, 2012.
- T.Liu, A. W. Moore, A. Gray, and K. Yang, "An Investigation of Practical Approximate Nearest Neighbor Algorithms," Proc. of NIPS, pp.825-832. 2005.
- W. Liu, J. Wang, S. Kumar, and S.-F. Chang, "Hashing with Graphs," Proc. of Int. Conf. on Machine Learning, 2011.
- U. von Luxburg, "A Tutorial on Spectral Clustering," Stat. Comput., vol.17, pp. 395-416, 2007. https://doi.org/10.1007/s11222-007-9033-z
- U. Manber, "Finding Similar Files in a Large File System," Proc. USENIX Conference, pp. 1-10, 1994.
- Y. Matsushita and T. Wada, "Principal Component Hashing: An Accelerated Approximate Nearest Neighbor Search," Proc. of PSIVT, 2009.
- B. McFee and G. Lanckriet, "Large-Scale Music Similarity Search With Spatial Trees," Proc. of ISMIR, 2011.
- G. A. Miller, R. Beckwith, C. D. Fellbaum, D. Gross, and K. Miller, "WordNet: An Online Lexical Database," Int. J. Lexicograph, vol.3, no.4, pp. 235-244, 1990. https://doi.org/10.1093/ijl/3.4.235
- Y. Mu, J. Shen, and S. Yan, "Weakly-Supervised Hashing in Kernel Space," Proc. of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.3344-3351, 2010.
- D. Nister and H. Stewenius, "Scalable Recognition with a Vocabulary Tree," Proc. CVPR , vol. 5, 2006.
- M. Norouzi and D. J. Fleet, "Minimal Loss Hashing for Compact Binary Codes," Proc. of ICML, 2011.
- A. Oliva, A. Torralba, "Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope," Int. J. of Computer Vision, vol.42,no.3, pp.145-175, 1989.
- S. Omohundro, "Five balltree construction algorithms," Technical Report, ICSI, 1989.
- S. Pandey, A. Broder, and F. Chierichetti, "Nearest-Neighbor Caching for Content-Match Applications," Proc. of WWW Conf., 2009.
- M. Potthast and B. Stein, "New Issues in Near-Duplicate Detection," Data Analysis, Machine Learning and Applications, pp. 601-609, Springer, 2008.
- M. Raginsky, and S. Lazebnik, "Locality-sensitive binary codes from shift-invariant kernels," Proc. of NIPS, 2009.
- B. C. Russell, A. Torralba, K. P. Murphy, and W. T. Freeman, LabelMe, http://labelme.csail.mit.edu/.
- R. R. Salakhutdinov and G.E. Hinton, "Semantic hashing," Proc. of Int.l J. of Approximate Reasoning, vol.50, no.7, 2009.
- R. E. Schapire, "The Boosting Approach to Machine Learning : An Overview," Nonlinear Estimation and Classification, Springer, 2003.
- G. Shakhnarovich, P. Viola, and T. Darrell, "Fast Pose Estimation with Parameter Sensitive Hashing," Proc. ICCV, 2003.
- B. Stein, S. M. Eissen, and M. Potthas, "Strategies for retrieving plagiarized documents," SIGIR, 2007.
- C. Strecha, A. M. Bronstein, M. M. Bronstein, and P. Fua," LDAHash: Improved Matching with Smaller Descriptors," IEEE TPAMI, vol34, no.1, 2012.
- M. Tata, T. Muto, M. Iwamura, and K. Kise, "Extension of Approximate Nearest Neighbor Search Based on Multi-Valued Expression on Closeness to General Distributions," DEIM Forum, 2010(in Japanese).
- M. Theodbald, J. Siddhaarth, and A. Paepcke, "Spot-Sigs: robust and efficient near duplicate detection in large web collections," Proc. ACM SIGIR, Singapore, pp.563-570, 2008.
- A. Torralba, R. Fergus, and Y. Weiss, "Small Codes and Large Image Databases for Recognition," Proc. of CVPR, pp.1-8, 2008.
- A. Torralba, R. Fergus, and W. T. Freeman, 80 Million Tiny Images: A Large Data Set for Nonparametric Object and Scene Recognition," IEEE PAMI, vol.30, no.11, 2008.
- J. K. Uhlmann, "Satisfying general proximity/ similarity queries with metric trees," Information Processing Letters,, vol.4, pp.175-179, 1991.
- J.Wang, S. Kumar, and S.-F. Chang, "Sequential Projection Learning for Hashing with Compact Codes," Proc. of Int. Conf. on Machine Learning, 2010.
- J. Wang, S. Kumar, and S.-F. Chang, "Semi-Supervised Hashing for Large Scale Search," IEEE PAMI, vol.34, no.12, 2012.
- Y. Weiss, A. Torralba, and R. Fergus, "Spectral hashing," Proc. of Neural Information Processing Systems, pp.1753-1760, 2008.
- H. Xu, J. Wang, Z. Li, G. Zeng, S. Le, and N. Yu, "Complementary Hashing for Approximate Nearest Neighbor Search," Proc. of IEEE Int. Conf. on Computer Vision, 2011.
- D. Zhang, J. Wang, D. Cai, and J. Lu, "Self-taught hashing for fast similarity search," Proc. SIGIR, pp.18-25, 2010.
- D. Zhang, J. Wang, D. Cai, and J. Lu, "Laplacian Cohashing of Terms and Documents," Proc. ECIR2010, LNCS, vol.5993, pp.577-580, 2010.
Cited by
- Bucket-size balancing locality sensitive hashing using the map reduce paradigm pp.1573-7543, 2017, https://doi.org/10.1007/s10586-017-1013-2
- MapReduce-based storage and indexing for big health data pp.15320626, 2018, https://doi.org/10.1002/cpe.4854