The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
The nature of statistical learning theory
The nature of statistical learning theory
The SR-tree: an index structure for high-dimensional nearest neighbor queries
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Dimensionality reduction for similarity searching in dynamic databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
On the effects of dimensionality reduction on high dimensional similarity search
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Locally adaptive dimensionality reduction for indexing large time series databases
ACM Transactions on Database Systems (TODS)
The K-D-B-tree: a search structure for large multidimensional dynamic indexes
SIGMOD '81 Proceedings of the 1981 ACM SIGMOD international conference on Management of data
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
G-Tree: A New Data Structure for Organizing Multidimensional Data
IEEE Transactions on Knowledge and Data Engineering
Similarity Indexing with the SS-tree
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
M-tree: An Efficient Access Method for Similarity Search in Metric Spaces
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
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
Index-driven similarity search in metric spaces (Survey Article)
ACM Transactions on Database Systems (TODS)
A non-linear dimensionality-reduction technique for fast similarity search in large databases
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
A survey of top-k query processing techniques in relational database systems
ACM Computing Surveys (CSUR)
Minimum bounding boxes for regular cross-polytopes
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Micro-specialization: dynamic code specialization of database management systems
Proceedings of the Tenth International Symposium on Code Generation and Optimization
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Range queries based on L1 distance are a common type of queries in multimedia databases containing feature vectors. We propose a novel approach that transforms the feature space into a new feature space such that range queries in the original space are mapped into equivalent box queries in the transformed space. Since box queries are axes aligned, there are several implementational advantages that can be exploited to speed up the retrieval of query results. For two dimensional data the transformation is precise. For greater than two dimensions we propose a space transformation scheme based on disjoint planer rotation, and along with pruning query box the results are precise. Experimental results with large synthetic databases and some real databases show the effectiveness of the proposed transformation scheme. These experimental results have been corroborated with appropriate mathematical models.