Semantic Web Technologies for Big Data Modeling from Analytics Perspective: A Systematic Literature Review

Georgieva-Trifonova, Tsvetanka; Galabov, Miroslav

doi:10.22364/bjmc.2021.9.4.01

Cited by 4 publications

(2 citation statements)

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“…The purpose of ontology is to provide a common understanding of a domain that can be shared, reused, and exchanged between heterogeneous and distributed systems. The very purpose of ontologies implies an opportunity to overcome problems related to the main distinguishing characteristics of big data -variety, veracity, value, variability, which was confirmed by the conducted scientific review of the existing research experience in [11]. As a result, modeling and building ontologies in various domains support the management and analysis of big data.…”

Section: Semantic Cmss and Big Datamentioning

confidence: 85%

Research on Using Semantic Web Technologies in Content Management Systems

Georgieva-Trifonova¹,

Marinov²

2022

TEM Journal

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In the present paper, the usage of Semantic web technologies for the purposes of Content Management Systems (CMSs) is explored. A review of the research related to semantic CMS is performed. The distinguishing features between CMSs that support Semantic web technologies and native semantic CMSs are discussed. The possibilities of semantic CMSs to overcome the challenges posed by big data are considered.

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Section: Semantic Cmss and Big Datamentioning

confidence: 85%

Research on Using Semantic Web Technologies in Content Management Systems

Georgieva-Trifonova¹,

Marinov²

2022

TEM Journal

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“…On the other hand, the application of Semantic web technologies in various domains is considered in systematic literature reviews such as cloud computing (Brabra et al, 2016); formal education (Jensen, 2017); distance learning (Bashir and Warraich, 2020); internet of things (Rhayem et al, 2020); bibliographic databases (Georgieva-Trifonova et al, 2020); big data modeling from analytics perspective (Georgieva-Trifonova and Galabov, 2021); healthcare (Bahalul Haque et al, 2022); software accessibility evaluation (Estrada-Martínez et al, 2022).…”

Section: Related Workmentioning

confidence: 99%

Application of Semantic Web Technologies for Supporting Customer Relationship Management: a Systematic Literature Review

Georgieva-Trifonova,

Petrov,

Milev

2023

BRAIN

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The purpose of the present paper is to summarize the current state of the existing research on the application of Semantic web technologies in supporting customer relationship management. Its achievement includes providing answers to a set of research questions as a result of conducting a systematic literature review. A total of 44 scientific publications are identified as relevant to the topic and included in the review. Information is extracted from the selected literature sources, which is then summarized, systemized and analyzed according to the predefined research questions and finally reported. The conducted systematic literature review determines that the development of Semantic web technologies is provoked interest among researchers, as a result of which the advantages of using them for descriptions useful for various CRM purposes are investigated and practically confirmed. In addition to defining semantic models for descriptions supporting a variety of CRM activities and processes (such as customized products and services; supporting users of CRM systems; integrated offerings across channels; improved and innovative products and services; customer complaint management, etc.), various research works identify new approaches to support CRM, that can be achieved through the application of appropriate Semantic web technologies. The detailed study represented in this paper contributes to familiarization with the existing experience in the application of Semantic web technologies in supporting customer relationship management, as well as facilitates the discovery of trends and directions for future research. This is the reason for the expected interest from scientists whose research area cover the considered and similar fields; software engineers implementing CRM systems; data analysts exploring CRM domain.

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A review and classification of manufacturing ontologies

Sapel,

Molinas Comet,

Dimitriadis

et al. 2024

J Intell Manuf

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One core concept of Industry 4.0 is establishing highly autonomous manufacturing environments. In the vision of Industry 4.0, the product leads its way autonomously through the shopfloor by communicating with the production assets. Therefore, a common vocabulary and an understanding of the domain’s structure are mandatory, so foundations in the form of knowledge bases that enable autonomous communication have to be present. Here, ontologies are applicable since they define all assets, their properties, and their interconnection of a specific domain in a standardized manner. Reusing and enlarging existing ontologies instead of building new ontologies facilitates cross-domain and cross-company communication. However, the demand for reusing or enlarging existing ontologies of the manufacturing domain is challenging as no comprehensive review of present manufacturing domain ontologies is available. In this contribution, we provide a holistic review of 65 manufacturing ontologies and their classification into different categories. Based on the results, we introduce a priority guideline and a framework to support engineers in finding and reusing existent ontologies of a specific subdomain in manufacturing. Furthermore, we present 16 supporting ontologies to be considered in the ontology development process and eight catalogs that contain ontologies and vocabulary services.

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Semantic Web Technologies for Big Data Modeling from Analytics Perspective: A Systematic Literature Review

Cited by 4 publications

References 0 publications

Research on Using Semantic Web Technologies in Content Management Systems

Research on Using Semantic Web Technologies in Content Management Systems

Application of Semantic Web Technologies for Supporting Customer Relationship Management: a Systematic Literature Review

A review and classification of manufacturing ontologies

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