Multiattribute hashing using Gray codes
SIGMOD '86 Proceedings of the 1986 ACM SIGMOD international conference on Management of data
Fractals for secondary key retrieval
PODS '89 Proceedings of the eighth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
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
Linear clustering of objects with multiple attributes
SIGMOD '90 Proceedings of the 1990 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
Range queries in OLAP data cubes
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
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
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 pyramid-technique: towards breaking the curse of dimensionality
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
The Grid File: An Adaptable, Symmetric Multikey File Structure
ACM Transactions on Database Systems (TODS)
Multidimensional binary search trees used for associative searching
Communications of the ACM
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
The TV-tree: an index structure for high-dimensional data
The VLDB Journal — The International Journal on Very Large Data Bases - Spatial Database Systems
Improving the Query Performance of High-Dimensional Index Structures by Bulk-Load Operations
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
A Robust Multi-Attribute Search Structure
Proceedings of the Fifth International Conference on Data Engineering
Feature-Based Retrieval of Similar Shapes
Proceedings of the Ninth International Conference on Data Engineering
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
Incremental Clustering for Mining in a Data Warehousing Environment
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Fast Similarity Search in the Presence of Noise, Scaling, and Translation in Time-Series Databases
VLDB '95 Proceedings of the 21th 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
SSD '95 Proceedings of the 4th International Symposium on Advances in Spatial Databases
Multidimensional Binary Search Trees in Database Applications
IEEE Transactions on Software Engineering
Interval Sequences: An Object-Relational Approach to Manage Spatial Data
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
Variable granularity space filling curve for indexing multidimensional data
ADBIS'11 Proceedings of the 15th international conference on Advances in databases and information systems
Indexing RFID data using the VG-curve
ADC '12 Proceedings of the Twenty-Third Australasian Database Conference - Volume 124
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Efficient query processing is one of the basic needs for data mining algorithms. Clustering algorithms, association rule mining algorithms and OLAP tools all rely on efficient query processors being able to deal with high-dimensional data. Inside such a query processor, multidimensional index structures are used as a basic technique. As the implementation of such an index structures is a difficult and time-consuming task, we propose a new approach to implement an index structure on top of a commercial relational database system. In particular, we map the index structure to a relational database design and simulate the behavior of the index structure using triggers and stored procedures. This can easily be done for a very large class of multidimensional index structures. To demonstrate the feasibility and efficiency, we implemented an X-tree on top of Oracle 8. We ran several experiments on large databases and recorded a performance improvement of up to a factor of 11.5 compared to a sequential scan of the database.