2016Unpublished venueRequires access

Improving data structure operations for high dimensional data

Bhoomika Panchal, Vinit Kumar

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Abstract

Here, we focus on a search operation that performs on high dimensional dataset. Many indexing structure are there like R-tree and its variants that are not applicable for high dimensional dataset. When depth of tree increases than searching operation is take more time. Due to this we are using a new data structure R-train which improves the search complexity. That is also work with historical movements of objects and spatial objects of data structure operations. It also reduces the time taken by memory to fetch the data from the storage.

About this research paper

What this paper is about

Here, we focus on a search operation that performs on high dimensional dataset. Many indexing structure are there like R-tree and its variants that are not applicable for high dimensional dataset. When depth of tree increases than searching operation is take more time. Due to this we are using a new data structure R-train which improves the search complexity. That is also work with historical movements of objects and spatial objects of data structure operations. It also reduces the time taken by memory to fetch the data from the storage.

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Available abstract

Here, we focus on a search operation that performs on high dimensional dataset. Many indexing structure are there like R-tree and its variants that are not applicable for high dimensional dataset. When depth of tree increases than searching operation is take more time. Due to this we are using a new data structure R-train which improves the search complexity. That is also work with historical movements of objects and spatial objects of data structure operations. It also reduces the time taken by memory to fetch the data from the storage.

Key concepts: Computer science, Data structure, Search engine indexing, Focus (optics), Tree structure, Data mining, Fetch, Search tree

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