multi-dimensionaldatastructures are applied in many real index applications, i.e. data mining, indexing multimedia data, indexing of text documents and so on. Many index structures and algorithms have been proposed....
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ISBN:
(纸本)9780769525778
multi-dimensionaldatastructures are applied in many real index applications, i.e. data mining, indexing multimedia data, indexing of text documents and so on. Many index structures and algorithms have been proposed. There are two major approaches to multi-dimensional indexing: datastructures to indexing metric and vector spaces. R-trees, R*-trees and (B)UB-trees are representatives of the vector datastructures. These datastructures provide efficient processing of many types of queries, i.e. point queries, range queries and so on. As far as the vector datastructures are concerned, the range query retrieves all points in defined hyper box in an n-dimensional space. The narrow range query is an important type of the range query. Its processing is inefficient in vector datastructures. Moreover, the efficiency decreases as the dimension of the indexed space increases. We depict an application of the signature for more efficient processing of narrow range queries. The approach puts the signature into the multi-dimensionaldatastructures like R-tree or UB-tree but original functionalities are preserved, i.e. the range query algorithm for general range query. The novel datastructure is called the signature datastructure, e.g., Signature R-tree or Signature UB-tree.
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