- The ND-Tree: A Dynamic Indexing Technique for Multidimensional Non-ordered Discrete Data Spaces

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The similarity searches in multidimensional non-ordered discrete data spaces (NDDS) are becoming increasingly important for application areas such as genome sequence databases. Existing indexing methods developed for multidimensional (ordered) continuous data spaces (CDS) such as R-tree cannot be directly applied to an NDDS. This is because some essential geometric concepts/properties such as the minimum bounding region and the area of a region in a CDS are no longer valid in an NDDS. Whereas, indexing methods based on metric spaces such as M-tree are too general to effectively utilize the data distribution characteristics in an NDDS. Therefore, their retrieval performance is not optimized. To support efficient similarity searches in an NDDS, it proposes a new dynamic indexing technique, called the ND-tree. The key idea is to extend the relevant geometric concepts as well as some indexing strategies used in CDSs to NDDSs.

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