Dissimilarity based on direction information and its application

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2 Scopus citations

Abstract

Similarity (dissimilarity) is of critical importance for data analysis, especially for clustering problem. The classical dissimilarity is related to distance (norm of the difference between each pair of data points), but it ignores the direction information from one data point to another. In this paper, we proposed a new dissimilarity based on direction consistence, which considers not only the distance information but also the direction information. It has some advantages and can be used in clustering to give a good performance.

Original languageEnglish
Title of host publicationProceedings - 4th International Congress on Image and Signal Processing, CISP 2011
Pages134-138
Number of pages5
DOIs
StatePublished - 2011
Event4th International Congress on Image and Signal Processing, CISP 2011 - Shanghai, China
Duration: 15 Oct 201117 Oct 2011

Publication series

NameProceedings - 4th International Congress on Image and Signal Processing, CISP 2011
Volume1

Conference

Conference4th International Congress on Image and Signal Processing, CISP 2011
Country/TerritoryChina
CityShanghai
Period15/10/1117/10/11

Keywords

  • affecting field
  • clustering
  • direction consistent
  • nearest neighborhood

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