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86748

BIO-INSPIRED COMPUTING VIA ONTOLOGY TO ENHANCE TAKING A DECISION ON HETEROGENEOUS DATA

Article

Last updated: 22 Jan 2023

Subjects

-

Tags

Mathematics

Abstract

Although Ontology supports phases of the decision support systems DSSs, there isn't a standard method in which we could modeled decisions in Ontologies. Heterogeneity in data sources is a challenge in decision support systems. Sometimes, explore the knowledge without integrating data sources is wrong. So, this paper proposed a semantic enhancement on the genotype/phenotype system. That is for a communication decision support system based on the Ontology decision support system framework ODSS. This paper introduced a compact representation, and a search strategy based on the universal Ontology. The proposed method is general to handle any data mining technique on large heterogeneous data. That is by adapting the components of the Gene Expression system in biology. The main components of the Gene Expression system are Genome, phenotype, and mutation. The adaptation is by Ontology to help the communication decision support system. The method adapts mutation as a somatic mutation. We tested the proposed method by applying it on the big sample of heterogeneous communication data. 

DOI

10.21608/absb.2019.86748

Keywords

Decision support system, ontology, Association Rules, Somatic mutation, genotype/phenotype

Authors

First Name

Eman

Last Name

Elsayed

MiddleName

K.

Affiliation

Mathematical Department, faculty of science (girls), Al-Azhar University

Email

emankaran10@azhar.edu.eg

City

Cairo

Orcid

0000-0001-7870-927X

Volume

30

Article Issue

2-B

Related Issue

13036

Issue Date

2019-12-01

Receive Date

2019-08-12

Publish Date

2019-12-01

Page Start

29

Page End

36

Print ISSN

1110-2535

Online ISSN

2636-3305

Link

https://absb.journals.ekb.eg/article_86748.html

Detail API

https://absb.journals.ekb.eg/service?article_code=86748

Order

3

Type

Original Article

Type Code

520

Publication Type

Journal

Publication Title

Al-Azhar Bulletin of Science

Publication Link

https://absb.journals.ekb.eg/

MainTitle

-

Details

Type

Article

Created At

22 Jan 2023