Isotropic Dynamic Hierarchical Clustering

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Victor Sadikov
Victor Sadikov
2
Oliver Rutishauser
Oliver Rutishauser

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GJCST Volume 16 Issue C3

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We face a business need of discovering a pattern in locations of a great number of points in a high-dimensional space. We assume that there should be a certain structure, so that in some locations the points are close while in other locations the points are more dispersed. Our goal is to group the close points together. The process of grouping close objects is known under the name of clustering.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

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Not applicable for this article.

Victor Sadikov. 2016. \u201cIsotropic Dynamic Hierarchical Clustering\u201d. Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 16 (GJCST Volume 16 Issue C3): .

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GJCST Volume 16 Issue C3
Pg. 29- 36
Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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GJCST-C Classification: H.3.3, I.5.3
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v1.2

Issue date

July 1, 2016

Language

English

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We face a business need of discovering a pattern in locations of a great number of points in a high-dimensional space. We assume that there should be a certain structure, so that in some locations the points are close while in other locations the points are more dispersed. Our goal is to group the close points together. The process of grouping close objects is known under the name of clustering.

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Isotropic Dynamic Hierarchical Clustering

Victor Sadikov
Victor Sadikov
Oliver Rutishauser
Oliver Rutishauser

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