Map Similarity Testing Using Matrix Decomposition

The similarity of two maps can be most easily compared visually. In this case, the degree of similarity is very subjective. It is therefore necessary to find an objective method for measuring similarity. This paper presents a method based on Singular Value Decomposition (SVD).

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Published in2009 International Conference on Intelligent Networking and Collaborative Systems pp. 290 - 294
Main Authors Dvorský, Jirí, Snášel, Václav, Voženílek, Vít
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2009
Subjects
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ISBN9781424451654
1424451655
DOI10.1109/INCOS.2009.74

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Abstract The similarity of two maps can be most easily compared visually. In this case, the degree of similarity is very subjective. It is therefore necessary to find an objective method for measuring similarity. This paper presents a method based on Singular Value Decomposition (SVD).
AbstractList The similarity of two maps can be most easily compared visually. In this case, the degree of similarity is very subjective. It is therefore necessary to find an objective method for measuring similarity. This paper presents a method based on Singular Value Decomposition (SVD).
Author Snášel, Václav
Voženílek, Vít
Dvorský, Jirí
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  givenname: Vít
  surname: Voženílek
  fullname: Voženílek, Vít
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Snippet The similarity of two maps can be most easily compared visually. In this case, the degree of similarity is very subjective. It is therefore necessary to find...
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StartPage 290
SubjectTerms air temperature
climatic maps
Intelligent networks
International collaboration
Matrix decomposition
Payloads
Real time systems
Singular Value Decomposition
Streaming media
Telecommunication traffic
Testing
Unicast
Web and internet services
Title Map Similarity Testing Using Matrix Decomposition
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