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Distributed indexing method for large-scale high-dimensional spatial data

A high-dimensional space, distributed technology, applied in the Internet field to achieve good performance, improved insertion and query operations, and reduced time consumption

Active Publication Date: 2016-11-09
SICHUAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

How to carry out distributed parallel metric space indexing, domestic and foreign scholars have little research

Method used

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  • Distributed indexing method for large-scale high-dimensional spatial data
  • Distributed indexing method for large-scale high-dimensional spatial data
  • Distributed indexing method for large-scale high-dimensional spatial data

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Embodiment Construction

[0041] All features disclosed in this specification, or all disclosed steps in a method or process, may be combined in any way except mutually exclusive features and / or steps.

[0042] Any feature disclosed in this specification (including any accompanying claims, abstract and drawings), unless expressly stated otherwise, may be replaced by other equivalent or alternative features serving a similar purpose. That is, unless expressly stated otherwise, each feature is but one example of a series of equivalent or similar features.

[0043] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0044] First disclose relevant concepts and problem definitions

[0045] The present invention mainly defines and explains some basic concepts in the system model, including metric space definition, nearest neighbor query and multi-dominant point tree construction and query algorithm.

[0046] In m...

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Abstract

The invention discloses a distributed indexing method for large-scale high-dimensional spatial data. The method includes the following steps that 1, advantageous points N are selected and divided according to an edge selection method in a metric space; 2, the metric space is divided into 2<n> sub spaces according to the selected advantageous points in the metric space; 3, after the space is divided, a main space indexing tree is constructed on a main guiding host according to the divided space structures; 4, all sub spaces are distributed to corresponding 2<n> subsidiary nodes, and a multi-advantageous-point tree is conducted on a subsidiary-node machine; 5, when an object in a new metric space is inserted into the distributed type multi-advantageous tree indexing structure, the insert request is sent to the main guiding host in the first place. The proposed distributed type multi-advantageous-point tree model has good performance, and time consumption of the multi-advantageous-point tree is reduced by half compared with a distributed type multi-advantageous-point tree (1, 2) model.

Description

technical field [0001] The invention relates to the field of Internet technology, in particular to a distributed indexing method for large-scale high-dimensional spatial data. Background technique [0002] With the rapid development of wireless communication technology and mobile terminal technology, the mobile Internet came into being and developed rapidly. What follows is the rapid expansion of data volume, which brings serious challenges to traditional data processing methods. In the metric space, how to perform similarity retrieval of high-dimensional vectors has always been a hot topic in the field of data processing and retrieval. It has a wide range of applications in geographic information systems, image retrieval, multimedia databases, pattern recognition, very large-scale integrated circuits, biological gene databases and many other fields. The high-dimensional features are extracted from the music melody, and then the melody of the user's humming song is also ex...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/2246G06F16/2264
Inventor 李川王昂
Owner SICHUAN UNIV