Efficient and effective querying by image content
Journal of Intelligent Information Systems - Special issue: advances in visual information management systems
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
The TV-tree: an index structure for high-dimensional data
The VLDB Journal — The International Journal on Very Large Data Bases - Spatial Database Systems
A Multistep Approach for Shape Similarity Search in Image Databases
IEEE Transactions on Knowledge and Data Engineering
Efficient Color Histogram Indexing for Quadratic Form Distance Functions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Similarity Indexing with the SS-tree
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Improving Adaptable Similarity Query Processing by Using Approximations
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
MindReader: Querying Databases Through Multiple Examples
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
The X-tree: An Index Structure for High-Dimensional Data
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Efficient User-Adaptable Similarity Search in Large Multimedia Databases
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
3D Shape Histograms for Similarity Search and Classification in Spatial Databases
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
Independent Quantization: An Index Compression Technique for High-Dimensional Data Spaces
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Spin Images and Neural Networks for Efficient Content-Based Retrieval in 3D Object Databases
CIVR '02 Proceedings of the International Conference on Image and Video Retrieval
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Adaptable similarity queries based on quadratic form distance functions are widely popular in data mining applications, particularly for domains such as multimedia, CAD, molecular biology or medical image databases. Recently it has been recognized that quantization of feature vectors can substantially improve query processing for Euclidean distance functions, as demonstrated by the scan-based VA-file and the index structure IQ-tree. In this paper, we address the problem that determining quadratic form distances between quantized vectors is difficult and computationally expensive. Our solution provides a variety of new approximation techniques for quantized vectors which are combined by an extended multistep query processing architecture. In our analysis section we show that the filter steps complement each other. Consequently, it is useful to apply our filters in combination. We show the superiority of our approach over other architectures and over competitive query processing methods. In our experimental evaluation, the sequential scan is outperformed by a factor of 2.3. Compared to the X-tree, on 64 dimensional color histogram data, we measured an improvement factor of 5.6.