Deriving an ontology for knowledge management in collaborative innovation networks

Barradas, Luís C. S.; Rodrigues, Eduarda Mendes; Ferreira, João José Pinto

doi:10.1504/ijil.2016.075658

Cited by 6 publications

(5 citation statements)

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“…3 Currently, the research of ontology knowledge has made considerable progress in biology, medicine, aviation, and some other fields. 4 Specifically, in the field of coal mining safety, the ontology and rule reasoning-based knowledge base can be established through the construction of mine motor fault-knowledge domain ontology. 5 A mine hoist fault diagnosis ontology knowledge base was constructed, and an ontology mapping-based fault diagnosis method was proposed.…”

Section: Related Workmentioning

confidence: 99%

“…As a knowledge organization model, ontology knowledge provides a good carrier for the knowledge‐based realization of knowledge acquisition, organization, representation, and reuse 3 . Currently, the research of ontology knowledge has made considerable progress in biology, medicine, aviation, and some other fields 4 . Specifically, in the field of coal mining safety, the ontology and rule reasoning‐based knowledge base can be established through the construction of mine motor fault‐knowledge domain ontology 5 .…”

Section: Related Workmentioning

confidence: 99%

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An intelligent recommendation method for coal mine accident case via ontology knowledge service

Luo

Zhang²,

Chen

2023

Engineering Reports

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Coal mine accidents, for example, water leakage and collapse, can damage the circuit system, and they in turn can affect the stable operation of the coal mine. Therefore, it is necessary to identify the causes of coal mine accidents and reduce the number of accidents in coal mines. Government and enterprises have already accumulated numerous coal mine accident cases. To summarize the characteristics and rules of accidents, survey the deep cause of the accident, avoid the recurrence of similar accidents, and early pre‐control of risk source, there is a need to analyze the correlation in the accident characteristics. Then, with the help of ontology knowledge service model, we address this issue in this article. For guaranteeing the inference efficiency of ontology knowledge, we propose a semiautomatic construction method for coal mine accident cases to construct ontology. Here, the reliability of ontology construction and the professionalism of domain knowledge provide a feasible approach to ontology learning using structured and semi‐structured data sources. Furthermore, the weighted Word2vec and spectral clustering method are combined, an intelligent recommendation algorithm with accident ontology is accordingly presented, while presenting a local optimal distance calculation similarity strategy. This method can serve as an assistant to help users mine similar coal mine accident cases. Finally, the experimental results show that after comparing with some other popular methods, the proposed approach can achieve a satisfactory performance on the coal mine dataset with an accuracy of 99.47%, the precision of 98.92%, and the F1‐score of 99.35.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

An intelligent recommendation method for coal mine accident case via ontology knowledge service

Luo

Zhang²,

Chen

2023

Engineering Reports

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“…Similarly, in the collaborative design domain involving knowledge management, researchers were focusing on strategic approaches to enable wider knowledge networks, often resulting in additional data and information [9], than focusing on appropriation methods. On the other hand, open innovation systems in collaborative engineering promise some key enablers in ontology linking [10]. For example, Semantic web technologies offer the ability to link data effectively across independent noninteroperable information and communication technologies (ICT) using existing online enterprise network capabilities [11].…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, open innovation systems in collaborative engineering promise some key enablers in ontology linking. 10 For example, Semantic web technologies offer the ability to link data effectively across independent non-interoperable information and communication technologies (ICT) using existing online enterprise network capabilities. 11 An example of this is its expansion into social networks operating to exchange general product updates via social activities.…”

Section: Introductionmentioning

confidence: 99%

A design for manufacturing methodology using defects knowledge for aerospace product manufacturing

Elsouri

Gao

Simmonds

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part B:

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Defects generated by the UK supply chain is much higher than its global competitors. Defects impact costs and production throughput due to unpredictable disruptions resulting in many non-value adding activities. However, defects data associated knowledge have rarely been considered and implemented as the manufacturing capability in existing design for manufacturing and assembly (DFMA) data/knowledge bases. On the other hand, current ICT systems used in the aerospace industry are not flexible enough to keep up with the new requirements of collaborating to manage knowledge properly, and the use of real-time manufacturing data generated in manufacturing activities. This research was carried out in collaboration with one of the UK’s largest aerospace companies in order to analyse the complexity of design and manufacturing activities of high-value safety-critical aerospace products. The results of the work are presented, and a novel approach and system was developed, that can be used to support DFMA using defects knowledge. The approach was implemented as a knowledge management system using collaborative design principles. Key findings from the main contribution in the context of extended enterprises of high value low volume safety critical product manufacturing are discussed.

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“…In order to find learning materials that are suitable for a staff member to learn, a user model has to be established to assess his/her skills on various topics. In online systems, users' interaction records with the system are a handy source for user modelling, from which behavioural patterns can be extracted to map their interests/knowledge to a topic ontology (Kim and Chan, 2008;Barradas et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Topic-aware staff learning material generation in complaint management systems

Junmin

Meng

et al. 2018

IJIL

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In this paper, a topic-aware staff learning material generation approach is proposed in complaint management systems. Historical processing logs are extracted to form a complaint space. Complaint processing skills of staff members are assessed in terms of quantity, efficiency and quality on various topics. Similar staff members are clustered according to their behavioural characteristics. A resource recommendation algorithm is proposed to recommend complaint processing records from highly skilled colleagues in the cluster for the staff member to learn. Preliminary experiment results show good performance of the proposed method.

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Deriving an ontology for knowledge management in collaborative innovation networks

Cited by 6 publications

References 0 publications

An intelligent recommendation method for coal mine accident case via ontology knowledge service

An intelligent recommendation method for coal mine accident case via ontology knowledge service

A design for manufacturing methodology using defects knowledge for aerospace product manufacturing

Topic-aware staff learning material generation in complaint management systems

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