A proposed algorithm for clustering data based on relations among points

Joint Authors

Miftin, Firas Sabar
Nasir, Mustafa A.

Source

Journal of College of Education for Pure Sciences

Issue

Vol. 10, Issue 1 (31 Mar. 2020), pp.27-35, 9 p.

Publisher

University of Thi-Qar College of Education for Pure Sciences

Publication Date

2020-03-31

Country of Publication

Iraq

No. of Pages

9

Main Subjects

Information Technology and Computer Science

Abstract EN

This paper deals with automatic clustering algorithm, which partitions a many of objects to get smaller sets (clusters).

Where objects of the one set are related to each other rather than to those in the other sets.

The number of clusters in automatic clustering don’t given priori, they determinates automatically, the number resulted of clusters exact closed to the numbers of the real dataset structure.

This paper represents a stimulus for the current study to introduce an algorithm that automatically finds the number of clusters based on distance among vertices.

The study is based on the hypothesis that the proposed algorithm is able to efficiently find the clustering partitions for the whole dataset.

American Psychological Association (APA)

Nasir, Mustafa A.& Miftin, Firas Sabar. 2020. A proposed algorithm for clustering data based on relations among points. Journal of College of Education for Pure Sciences،Vol. 10, no. 1, pp.27-35.
https://search.emarefa.net/detail/BIM-1383747

Modern Language Association (MLA)

Nasir, Mustafa A.& Miftin, Firas Sabar. A proposed algorithm for clustering data based on relations among points. Journal of College of Education for Pure Sciences Vol. 10, no. 1 (Mar. 2020), pp.27-35.
https://search.emarefa.net/detail/BIM-1383747

American Medical Association (AMA)

Nasir, Mustafa A.& Miftin, Firas Sabar. A proposed algorithm for clustering data based on relations among points. Journal of College of Education for Pure Sciences. 2020. Vol. 10, no. 1, pp.27-35.
https://search.emarefa.net/detail/BIM-1383747

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references : p. 33-35

Record ID

BIM-1383747