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 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
The string B-tree: a new data structure for string search in external memory and its applications
Journal of the ACM (JACM)
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
Converting numerical classification into text classification
Artificial Intelligence
On Changing Continuous Attributes into Ordered Discrete Attributes
EWSL '91 Proceedings of the European Working Session on Machine Learning
Similarity Indexing with the SS-tree
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
The LSDh-Tree: An Access Structure for Feature Vectors
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
The R+-Tree: A Dynamic Index for Multi-Dimensional Objects
VLDB '87 Proceedings of the 13th 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
The Hybrid Tree: An Index Structure for High Dimensional Feature Spaces
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
A survey of evolutionary algorithms for data mining and knowledge discovery
Advances in evolutionary computing
A space-partitioning-based indexing method for multidimensional non-ordered discrete data spaces
ACM Transactions on Information Systems (TOIS)
ACM Transactions on Database Systems (TODS)
Indexing and Integrating Multiple Features for WWW Images
World Wide Web
The ND-tree: a dynamic indexing technique for multidimensional non-ordered discrete data spaces
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
| Hi-index | 0.00 |
Contemporary database applications often perform queries in hybrid data spaces (HDS) where vectors can have a mix of continuous valued and non-ordered discrete valued dimensions. To support efficient query processing for an HDS, a robust indexing method is required. Existing indexing techniques to process queries efficiently either apply to continuous data spaces (e.g., the R-tree) or non-ordered discrete data spaces (e.g., the ND-tree). No techniques directly indexing vectors in HDSs have been reported in the literature. In this paper, we propose a new multidimensional indexing technique, called the C-ND tree, to directly index vectors in an HDS. To build such an index, we first introduce some essential geometric concepts (e.g., hybrid bounding rectangle) in HDSs. The C-ND tree structure and the relevant tree building and query processing algorithms based on these geometric concepts in HDSs are then presented. Strategies have been suggested to make the values in continuous dimensions and non-ordered discrete dimensions comparable and controllable. Novel node splitting heuristics which exploit characteristics of both continuous and discrete dimensions are proposed. Performance of the C-ND tree is compared with that of linear scan, R*-tree and ND-tree using range queries on hybrid data. Experimental results demonstrate that the C-ND tree is quite promising in supporting range queries in HDSs.