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Applied Sciences
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Ontology Engineering and Knowledge Graphs Design in Decision Support Systems:...
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Ontology Engineering and Knowledge Graphs Design in Decision Support Systems: Novel Advances and Use-Cases

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (15 February 2023) | Viewed by 11396

Special Issue Editor

Prof. Dr. Lina Soualmia

E-Mail Website
Guest Editor
Department of Computer Science and Biomedical Inforlatics, Université de Rouen Normandie, Rouen, France
Interests: knowledge representation; medical ontologies; information retrieval

Special Issue Information

Dear Colleagues,

Decision support systems have been developed in several domains (healthcare, industry, etc.) to solve problems and help in decision making, knowledge representation often playing an important role in these systems. Knowledge can be represented in knowledge graphs as well as structured formats such as ontologies, which ease search and reasoning tasks.

This Special Issue invites original, high-quality work presenting novel research and/or real use cases regarding ontology engineering, knowledge graph design, management and querying and their use in decision support systems.

Topics for this Special Issue include, but are not limited to, novel advances in:

  • Ontology engineering and reasoning for decision making;
  • Knowledge integration, representation and inference;
  • Heterogenous data integration (multi-scale, multi-modal, etc.);
  • Knowledge graphs construction, management and querying for decision support systems;
  • Domain applications in healthcare, imaging, environment, industry, etc.

Prof. Dr. Lina Soualmia
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • ontologies
  • semantic web
  • knowledge graphs
  • logic-based reasoning
  • expert systems
  • decision support systems

Published Papers (6 papers)

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Research

18 pages, 858 KiB  
Article
AI4PD—Towards a Standardized Interconnection of Artificial Intelligence Methods with Product Development Processes
by Benjamin Gerschütz, Stefan Goetz and Sandro Wartzack
Appl. Sci. 2023, 13(5), 3002; https://0-doi-org.brum.beds.ac.uk/10.3390/app13053002 - 26 Feb 2023
Cited by 3 | Viewed by 1740
Abstract
The transformation of virtual product development to Digital Engineering (DE) requires the successful integration of Digital Engineering or data-driven methods into existing product development processes. Those methods allow for the analysis and usage of existing data. However, missing knowledge about these methods, as [...] Read more.
The transformation of virtual product development to Digital Engineering (DE) requires the successful integration of Digital Engineering or data-driven methods into existing product development processes. Those methods allow for the analysis and usage of existing data. However, missing knowledge about these methods, as well as their performance or limitations, is a major burden for their application, especially in small and medium-sized enterprises. In order to close this gap, this paper proposes the AI4PD ontology, linking product development processes (PD) and Digital Engineering methods (AI). This knowledge representation gives companies an overview of the available methods to support them in selecting a suitable solution for their problems. The representation of AI4PD is performed in Protégé using the W3C standard OWL syntax. The opportunities of AI4PD are shown by a use case of identifying a DE-Method for predicting manufacturing possibilities based on test data and CAD files. Furthermore, after possible problems in existing product development processes are identified, AI4PD covers the necessary knowledge for a successful method of identification and integration to transform virtual product development to Digital Engineering. Full article
(This article belongs to the Special Issue Ontology Engineering and Knowledge Graphs Design in Decision Support Systems: Novel Advances and Use-Cases)
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17 pages, 959 KiB  
Article
A Semantic Model for Enhancing Data-Driven Open Banking Services
by Manuel Paneque, María del Mar Roldán-García and José García-Nieto
Appl. Sci. 2023, 13(3), 1447; https://0-doi-org.brum.beds.ac.uk/10.3390/app13031447 - 21 Jan 2023
Cited by 3 | Viewed by 2014
Abstract
In current Open Banking services, the European Payment Services Directive (PSD2) allows the secure collection of bank customer information, on their behalf and with their consent, to analyze their financial status and needs. The PSD2 directive has lead to a massive number of [...] Read more.
In current Open Banking services, the European Payment Services Directive (PSD2) allows the secure collection of bank customer information, on their behalf and with their consent, to analyze their financial status and needs. The PSD2 directive has lead to a massive number of daily transactions between Fintech entities which require the automatic management of the data involved, generally coming from multiple and heterogeneous sources and formats. In this context, one of the main challenges lies in defining and implementing common data integration schemes to easily merge them into knowledge-base repositories, hence allowing data reconciliation and sophisticated analysis. In this sense, Semantic Web technologies constitute a suitable framework for the semantic integration of data that makes linking with external sources possible and enhances systematic querying. With this motivation, an ontology approach is proposed in this work to operate as a semantic data mediator in real-world open banking operations. According to semantic reconciliation mechanisms, the underpinning knowledge graph is populated with data involved in PSD2 open banking transactions, which are aligned with information from invoices. A series of semantic rules is defined in this work to show how the financial solvency classification of client entities and transaction concept suggestions can be inferred from the proposed semantic model. Full article
(This article belongs to the Special Issue Ontology Engineering and Knowledge Graphs Design in Decision Support Systems: Novel Advances and Use-Cases)
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16 pages, 2436 KiB  
Article
An Approach to the Semantic Representation of the Local Government Strategic Planning Process: Ontology-Driven Simulation Method for Assessing Economic Impacts
by Miroslav Zarić, Saša Arsovski, Branko Markoski, Petar Vasiljević and Velibor Premčevski
Appl. Sci. 2023, 13(3), 1258; https://0-doi-org.brum.beds.ac.uk/10.3390/app13031258 - 17 Jan 2023
Cited by 1 | Viewed by 1007
Abstract
This paper describes a methodological approach to the creation of a strategic planning ontology (SPO) for local governments. The aim of the given ontology is to provide a semantic description of the development strategy, involved stakeholders, and tools to improve the decision-making process [...] Read more.
This paper describes a methodological approach to the creation of a strategic planning ontology (SPO) for local governments. The aim of the given ontology is to provide a semantic description of the development strategy, involved stakeholders, and tools to improve the decision-making process for selecting the most valuable strategic objectives for the economy of the region. The novelty of the research presented in this paper is reflected by the development of an ontological model of actions and reasons, that is, semantically described combinations of activities and requirements that are defined by development strategies. The proposed ontology can provide answers to questions such as: what are the development priorities? How will those priorities be implemented? Who will be responsible for implementation? Why are they being implemented in the first place? We answer the question, “why specific development goals are chosen?”. Answers are given as semantic representations of the economic impact on a region’s industry. The ontology-driven simulation methods that are proposed in this paper provide the possibility of simulating the effects and results of the chosen development strategy goals, evaluate the actions taken, and ensure support for the selection of the best alternative in the process of defining objectives for the development strategy. Full article
(This article belongs to the Special Issue Ontology Engineering and Knowledge Graphs Design in Decision Support Systems: Novel Advances and Use-Cases)
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19 pages, 1418 KiB  
Article
Entity Recognition for Chinese Hazardous Chemical Accident Data Based on Rules and a Pre-Trained Model
by Hui Dai, Mu Zhu, Guan Yuan, Yaowei Niu, Hongxing Shi and Boxuan Chen
Appl. Sci. 2023, 13(1), 375; https://0-doi-org.brum.beds.ac.uk/10.3390/app13010375 - 28 Dec 2022
Cited by 3 | Viewed by 2282
Abstract
Due to the fragile physicochemical properties of hazardous chemicals, the chances of leakage and explosion during production, transportation, and storage are quite high. In recent years, hazardous chemical accidents have occurred frequently, posing a great threat to people’s lives and property. Hence, it [...] Read more.
Due to the fragile physicochemical properties of hazardous chemicals, the chances of leakage and explosion during production, transportation, and storage are quite high. In recent years, hazardous chemical accidents have occurred frequently, posing a great threat to people’s lives and property. Hence, it is crucial to analyze hazardous chemical accidents and establish corresponding warning mechanisms and safeguard measures. At present, most hazardous-chemical-accident data exist in text format. However, named entity recognition (NER), as a method to extract useful information from text data, has not been fully utilized in the field of Chinese hazardous-chemical handling. The challenge is that Chinese NER is more difficult than English NER, because the boundaries of Chinese are fuzzy. In addition, the descriptions of hazardous chemical accidents are colloquial and lacks relevant labeling data. Further, most current models do not consider identifying the entities related to accident scenarios, losses, and causes. To tackle these issues, we propose a model based on a rule template and Bert-BiLSTM-CRF (RT-BBC) to recognize named entities from unstructured Chinese hazardous chemical accident reports. Comprehensive experiments on real-world datasets show the effectiveness of the proposed method. Specifically, RT-BBC outperformed the most competitive method by 6.6% and 3.6% in terms of accuracy and F1. Full article
(This article belongs to the Special Issue Ontology Engineering and Knowledge Graphs Design in Decision Support Systems: Novel Advances and Use-Cases)
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18 pages, 3044 KiB  
Article
An Enhanced Information Retrieval Method Based on Ontology for Bridge Inspection
by Yang Zhang, Yuhong Liu, Guangting Lei, Shengyu Liu and Peng Liang
Appl. Sci. 2022, 12(20), 10599; https://0-doi-org.brum.beds.ac.uk/10.3390/app122010599 - 20 Oct 2022
Cited by 2 | Viewed by 1509
Abstract
Bridge management systems (BMSs) are widely used to assist an inspector in performing element-level bridge inspection. Retrieving and determining target elements to be inspected becomes an important factor in the efficiency of bridge inspection. This paper presents an enhanced information retrieval (IR) method [...] Read more.
Bridge management systems (BMSs) are widely used to assist an inspector in performing element-level bridge inspection. Retrieving and determining target elements to be inspected becomes an important factor in the efficiency of bridge inspection. This paper presents an enhanced information retrieval (IR) method based on ontology to predict the target elements. The novelty of this method is that an improved seven-step method based on automatic mapping technology is proposed to construct a new bridge inspection ontology (BIontology), which provides a knowledge base for the present IR method. A further novelty is that a new software architecture is designed for integrating ontology, and a promising prototype system based on the software architecture is developed to realize the present IR method using SPARQL query. In addition, a novel prediction algorithm based on the present IR method is proposed to automatically recommend the target elements. A case study of ontology construction is performed to demonstrate that the improved seven-step method can accelerate the construction of the BIontology compared with the manual method. A case study of bridge inspection is implemented to verify that the proposed algorithm outperforms an existing method, thereby validating the effectiveness of the present IR method. Full article
(This article belongs to the Special Issue Ontology Engineering and Knowledge Graphs Design in Decision Support Systems: Novel Advances and Use-Cases)
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21 pages, 1230 KiB  
Article
Service Recommendations Using a Hybrid Approach in Knowledge Graph with Keyword Acceptance Criteria
by Jawad Ahmad, Abdur Rehman, Hafiz Tayyab Rauf, Kashif Javed, Maram Abdullah Alkhayyal and Abeer Ali Alnuaim
Appl. Sci. 2022, 12(7), 3544; https://0-doi-org.brum.beds.ac.uk/10.3390/app12073544 - 31 Mar 2022
Cited by 2 | Viewed by 1688
Abstract
Businesses are overgrowing worldwide; people struggle for their businesses and startups in almost every field of life, whether industrial or academic. The businesses or services have multiple income streams with which they generate revenue. Most companies use different marketing and advertisement strategies to [...] Read more.
Businesses are overgrowing worldwide; people struggle for their businesses and startups in almost every field of life, whether industrial or academic. The businesses or services have multiple income streams with which they generate revenue. Most companies use different marketing and advertisement strategies to engage their customers and spread their services worldwide. Service recommendation systems are gaining popularity to recommend the best services and products to customers. In recent years, the development of service-oriented computing has had a significant impact on the growth of businesses. Knowledge graphs are commonly used data structures to describe the relations among data entities in recommendation systems. Domain-oriented user and service interaction knowledge graph (DUSKG) is a framework for keyword extraction in recommendation systems. This paper proposes a novel method of chunking-based keyword extractions for hybrid recommendations to extract domain-specific keywords in DUSKG. We further show that the performance of the hybrid approach is better than other techniques. The proposed chunking method for keyword extraction outperforms the existing value feature entity extraction (VF2E) by extracting fewer keywords. Full article
(This article belongs to the Special Issue Ontology Engineering and Knowledge Graphs Design in Decision Support Systems: Novel Advances and Use-Cases)
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