Similarity measuring algorithm for sequences in different lengths

A similarity, long sequence technology, applied in the field of data fusion algorithms, can solve problems such as transformation errors, affecting the similarity measurement between sequences, and reducing the authenticity of data associations

Inactive Publication Date: 2014-08-13
关欣
View PDF0 Cites 12 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This kind of method is easy to introduce transformation error when transforming sequence data, which affects the similarity measurement between sequences, thereby reducing the authenticity of data association.

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
  • Similarity measuring algorithm for sequences in different lengths
  • Similarity measuring algorithm for sequences in different lengths
  • Similarity measuring algorithm for sequences in different lengths

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0061] Assuming that two types of sensors sensor1 and sensor2 are set as ESM and ELINT, the target is measured, and three types of target identity information are measured, radar carrier frequency RF, pulse repetition frequency PRF and pulse width PW, which are obtained after front-end data processing and correlation Two target sequence matrices S to be identified 1 and S 2 , which are composed of three bar sequences, representing RF, PRF and PW three types of parameters. There are four types of target identity attributes in the target database, and the sequence matrix Q 1 , Q 2 , Q 3 and Q 4 Indicates that the data parameters in the matrix and the target sequence matrix S to be identified are 1 and S 2 Correspondingly, the lengths between them are unequal. Adopt the method proposed by the present invention to calculate two target sequence matrices S to be identified 1 and S 2 and four types of target identity attribute sequence matrix Q 1 , Q 2 , Q 3 and Q 4 simi...

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 a similarity measuring algorithm for sequences in different lengths, in order to solve the similarity measuring problem of sequences in different lengths. The similarity measuring algorithm comprises the following steps: constructing a sliding window to traverse the sequences in different lengths; taking a sequence in short length as the sliding window; successively sliding for a unit length along the sequence in longer length till traversing the sequence in the whole length; calculating the similarity of the corresponding sequences in equal length during each traversing process, thereby forming sliding similarity; weighting and combing the similarity of all sliding areas through an optimal weight vector, thereby acquiring the similarity measure of the sequences in different lengths. According to the method, the similarity error is reduced and the adaptive control for similarity weighting is realized.

Description

technical field [0001] The invention relates to a data fusion algorithm, in particular to a data mining algorithm for unequal-length sequences. Background technique [0002] As a kind of uncertain data, sequence data is the main research object in the field of data mining, and widely exists in the fields of economic forecasting, medical research, weather forecasting, network security and military science. With the rapid development of information technology, the amount of data is increasing, and the information contained is also increasing, which undoubtedly entered the era of big data. How to mine effective information and knowledge hidden in these data has been extensively studied in recent years. Sequence data is high-dimensional data composed of many data points. The length of these data points may be inconsistent with time. Mining these sequence data with inconsistent length is a key issue in data mining. Sequence similarity measurement method is an important process ...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
Inventor 关欣孙贵东宋瑞华赵志勇衣晓
Owner 关欣
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