Automatic correlation method facing multivariate data

A multi-data, automatic association technology, applied in other database retrieval based on metadata, electronic digital data processing, other database retrieval, etc. multi-association issues

Active Publication Date: 2015-04-15
INST OF ELECTRONICS CHINESE ACAD OF SCI
View PDF3 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide an automatic association method for multivariate data, which solves the problem that the existing association method does not jointly consider mult

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Automatic correlation method facing multivariate data
  • Automatic correlation method facing multivariate data
  • Automatic correlation method facing multivariate data

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0025] The present invention will be described in detail below in combination with specific embodiments.

[0026] Such as figure 1 Shown, technical scheme of the present invention is as follows:

[0027] Step 1: Select multivariate data and define the basic structure of multivariate data. Multivariate data refers to different types of data with certain commonality. The basic structure of multivariate data is defined in combination with specific applications. Each data type should at least include attributes such as time, space, and labels. For example, image data includes time, space, and image attributes. Attributes such as length and width resolution, intelligence data include attributes such as time, space, and text content of intelligence;

[0028] Step 2: Extract the time attribute of each data. Extract the time attribute of each data and convert it to standard time, automatically complete the incomplete time attribute according to the context, and estimate the error r...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses an automatic correlation method facing multivariate data. The method includes selecting multivariate data, extracting time attribute of each data, conducting automatic supplementation with reference to the text for the data with insufficient time attribute, extracting the geometrical center position and the covering range of each data and converting the geometrical center position and the covering range to a unified oval coordinate system, adding attribute labels for the data, automatically adding the attribute labels for the data according to the source, the category, the class and the resolution of the data, wherein the data with identical labels have the implicit correlation; utilizing the multi-attribute information to excavate the correlation between the data, meanwhile considering the time attribute, the position attribute and the label information of the data, utilizing the improved distance to excavate the correlation between the data through the Chinese restaurant process, storing the correlation between the data as acknowledged information for follow-up automatic correlation. The method has the advantages of fully considering various attribute information to conduct data correlation to effectively utilize a large amount of information.

Description

technical field [0001] The invention belongs to the technical field of multivariate data automatic association, and relates to an automatic association method for multivariate data. Background technique [0002] With the development of aerospace technology and sensor technology, more and more remote sensing data can be obtained. How to automatically organize and manage these massive remote sensing data is the prerequisite for effective use. At the same time, these massive data come from different sensors, and the attribute elements of each sensor are also different, so the obtained data is also diverse. Multivariate data has different structural information, how to automatically organize and associate these data is the prerequisite for the effective use of information. [0003] At present, the association of multivariate data is mostly automatically associated based on specific attribute information. This association does not jointly consider multiple attribute information,...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06F17/30
CPCG06F16/907
Inventor 付琨许光銮孙显黄宇王磊田璟宋俊
Owner INST OF ELECTRONICS CHINESE ACAD OF SCI
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap