A Linked Data and Ontology-Based Framework for Enhanced Sharing of Safety Training Materials in the Construction Industry

Pedro, Akeem; Baik, Sangeun; Jo, Junhyeon; Lee, Doyeop; Hussain, Rahat; Park, Chansik

doi:10.1109/access.2023.3319090

Cited by 8 publications

(2 citation statements)

References 61 publications

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“…The domain of ontology supports the conceptualization of a certain domain of knowledge, and the efficiency of searching, accumulating, and sharing knowledge will thereby be significantly improved, promoting knowledge sharing [9,21]. In recent years, ontology has been widely used in academia, usually in fields such as architecture [22,23], artificial intelligence (AI) [24,25], and biomedicine [26,27], and with functions such as decision-making [28][29][30] and knowledge management [31,32].…”

Section: Application Of the Ontologymentioning

confidence: 99%

The Use of Weighted Euclidean Distance to Provide Assistance in the Selection of Safety Risk Prevention and Control Strategies for Major Railway Projects

Guo,

Lv,

et al. 2024

Buildings

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A major railway project is a complex, giant system with multi-party participation, one characterized by complex geological conditions, long construction periods and large scale, which leads to an increased likelihood of safety risk events during construction. In order to solve the problem of scientific selection and formulation of safety risk prevention and control strategies for major railway projects, an auxiliary selection method of safety risk prevention and control strategies for major railway projects based on weighted Euclidean distance (WED) is proposed. The relevant ontology is used to conceptualize and formalize the knowledge of safety risks of major railroad projects, and combine the characteristics of major railroad projects; it refers to the prevention and control measures of historical safety risk events associated with major railroad projects, and then constructs the knowledge structure and case base around safety risks of major railroad projects and the circumstances of the case. In determining the comprehensive weights, the G1 method is used to determine the subjective weights, the anti-entropy weight method is used to determine the objective weights and game theory combines the subjective and objective weights. In comparing the array of safety risk prevention and control cases associated with major railway projects, the weighted Euclidean distance is used to calculate the similarity between these cases and the target case, which in turn assists project managers in determining the safety risk prevention and control strategies appropriate for major railway projects. This study takes Landslide No. 1 in the Tunnel A inlet planning area as an example. It utilizes the WED method to assist in selecting safety risk prevention and control strategies for major railway projects, which verifies the method’s feasibility. The proposed method enriches the method of the assisted selection of safety risk prevention and control strategies for major railway projects, makes strategy formulation more scientific, has specific reference significance for the formulation of safety risk prevention and control strategies for major railway projects, and promotes the improvement of safety risk prevention and risk control for participating units.

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Section: Application Of the Ontologymentioning

confidence: 99%

The Use of Weighted Euclidean Distance to Provide Assistance in the Selection of Safety Risk Prevention and Control Strategies for Major Railway Projects

Guo,

Lv,

et al. 2024

Buildings

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“…For instance, there is a lack of comprehensive frameworks that can handle the diverse and dynamic nature of agricultural data samples [16]- [18]. There is a need for more sophisticated evaluation methods that can accurately assess the performance of ontology tools in real-world scenarios [19], [20].…”

Section: Literature Reviewmentioning

confidence: 99%

Enhancing Agricultural Knowledge Management using an efficient & Novel Ontology-Based Approach Leveraging BERT-GPT and Graph Recurrent Q Learning Network

2024

Journal of Electrical Systems

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Agriculture, as one of the key drivers for human civilization, demands efficient methods for managing the extensive domainspecific knowledge. While ontologies, structured sets of terms and relationships within a specific domain, have played a pivotal role in structuring agricultural data, existing models lack the precision and adaptability necessary for the dynamic agricultural environment. This paper proposes a novel framework that integrates the strengths of BERT (Bidirectional Encoder Representations from Transformers) GPT (Generative Pre-trained Transformer), and Graph Recurrent Q Learning Network (GRQLN) for developing a dynamic and efficient ontology tool. BERT-GPT, with its powerful natural language processing capabilities, allows for accurate feature extraction from diverse text data, including government and farming sources. Meanwhile, GRQLN leverages graph neural networks and reinforcement learning to convert these features into an ontology graph, optimizing the representation process. The integration of these advanced technologies not only addresses the limitations of existing models but also enhances the precision of ontological query retrieval by 8.5%, accuracy by 8.3%, recall by 10.4%, AUC by 9.5%, and specificity by 9.4%, while reducing delay by 4.5%. The proposed model is a significant contribution to the field, offering a robust tool that empowers stakeholders with actionable insights derived from a vast expanse of agricultural knowledge, ultimately facilitating informed decision-making in the ever-evolving landscape of agricultural operations.

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Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents

Shi,

Li,

Zurada

et al. 2024

Knowl Inf Syst

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A Linked Data and Ontology-Based Framework for Enhanced Sharing of Safety Training Materials in the Construction Industry

Cited by 8 publications

References 61 publications

The Use of Weighted Euclidean Distance to Provide Assistance in the Selection of Safety Risk Prevention and Control Strategies for Major Railway Projects

The Use of Weighted Euclidean Distance to Provide Assistance in the Selection of Safety Risk Prevention and Control Strategies for Major Railway Projects

Enhancing Agricultural Knowledge Management using an efficient & Novel Ontology-Based Approach Leveraging BERT-GPT and Graph Recurrent Q Learning Network

Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents

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