A Fast k Nearest Neighbor Finding Algorithm Based on the Ordered Partition
IEEE Transactions on Pattern Analysis and Machine Intelligence
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Fast parallel similarity search in multimedia databases
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Efficiently supporting ad hoc queries in large datasets of time sequences
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
A cost model for nearest neighbor search in high-dimensional data space
PODS '97 Proceedings of the sixteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Multidimensional access methods
ACM Computing Surveys (CSUR)
Hierarchical Discriminant Analysis for Image Retrieval
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Finding generalized projected clusters in high dimensional spaces
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From Statistics to Neural Networks: Theory and Pattern Recognition Applications
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Local Dimensionality Reduction: A New Approach to Indexing High Dimensional Spaces
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Similarity Search Using Multi-Space KL
DEXA '99 Proceedings of the 10th International Workshop on Database & Expert Systems Applications
The Hybrid Tree: An Index Structure for High Dimensional Feature Spaces
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Recursive partitioning to reduce distortion
IEEE Transactions on Information Theory
Addressing CBIR efficiency, effectiveness, and retrieval subjectivity simultaneously
MIR '03 Proceedings of the 5th ACM SIGMM international workshop on Multimedia information retrieval
GPCA: an efficient dimension reduction scheme for image compression and retrieval
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Generalized low rank approximations of matrices
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Segmentation and recognition of multi-attribute motion sequences
Proceedings of the 12th annual ACM international conference on Multimedia
Indexing of variable length multi-attribute motion data
Proceedings of the 2nd ACM international workshop on Multimedia databases
IDR/QR: An Incremental Dimension Reduction Algorithm via QR Decomposition
IEEE Transactions on Knowledge and Data Engineering
Exact k-NN queries on clustered SVD datasets
Information Processing Letters
Generalized Low Rank Approximations of Matrices
Machine Learning
Persistent clustered main memory index for accelerating k-NN queries on high dimensional datasets
Proceedings of the 2nd international workshop on Computer vision meets databases
Analytically tractable case of fuzzy c-means clustering
Pattern Recognition
Persistent clustered main memory index for accelerating k-NN queries on high dimensional datasets
Multimedia Tools and Applications
An information granulation based data mining approach for classifying imbalanced data
Information Sciences: an International Journal
Multimedia Tools and Applications
A simplified GLRAM algorithm for face recognition
Neurocomputing
Approximate similarity search: A multi-faceted problem
Journal of Discrete Algorithms
Adapting indexing trees to data distribution in feature spaces
Computer Vision and Image Understanding
Exact k-NN queries on clustered SVD datasets
Information Processing Letters
An incremental updating method for clustering-based high-dimensional data indexing
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Discriminating biased web manipulations in terms of link oriented measures
ISCIS'05 Proceedings of the 20th international conference on Computer and Information Sciences
Computer Vision and Image Understanding
Soft label based Linear Discriminant Analysis for image recognition and retrieval
Computer Vision and Image Understanding
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Nearest-neighbor search of high-dimensionality spaces is critical for many applications, such as content-based retrieval from multimedia databases, similarity search of patterns in data mining, and nearest-neighbor classification. Unfortunately, even with the aid of the commonly used indexing schemes, the performance of nearest-neighbor (NN) queries deteriorates rapidly with the number of dimensions. We propose a method, called Clustering with Singular Value Decomposition (CSVD), which supports efficient approximate processing of NN queries, while maintaining good precision-recall characteristics. CSVD groups homogeneous points into clusters and separately reduces the dimensionality of each cluster using SVD. Cluster selection for NN queries relies on a branch-and-bound algorithm and within-cluster searches can be performed with traditional or in-memory indexing methods. Experiments with texture vectors extracted from satellite images show that CSVD achieves significantly higher dimensionality reduction than plain SVD for the same Normalized Mean Squared Error (NMSE), which translates into a higher efficiency in processing approximate NN queries.