Automated conversion between different knowledge representation formats

Yao, Haining; Etzkorn, Letha H.

doi:10.1016/j.knosys.2006.04.005

Cited by 27 publications

(22 citation statements)

References 2 publications

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“…mapping properties into nested contexts) and in providing a visual reasoning that facilitates an intuitive understanding. In addition, conceptual graphs can be easily translated into the terminology of some other approaches in knowledge engineering, such as Resource Description Framework Schema (RDFS) [41] and its evolution, the Web Ontology Language (OWL) [42] mainly applied in connection with the Semantic Web framework [43]. As a result, it generates the possibility to interact and exchange the modeled knowledge with internal and external collaborators.…”

Section: Knowledge Representation Formalismsmentioning

confidence: 99%

Graph-based reasoning in collaborative knowledge management for industrial maintenance

Kamsu-Foguem

Noyes

2013

Computers in Industry

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Section: Knowledge Representation Formalismsmentioning

confidence: 99%

Graph-based reasoning in collaborative knowledge management for industrial maintenance

Kamsu-Foguem

Noyes

2013

Computers in Industry

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“…Furthermore, there is a formal correspondence between conceptual graphs and Description Logics that is the most implemented language in various knowledge base applications. Also, there are many mappings between conceptual graphs and languages associated to semantic web applications [20,21] (RDF(s) (Resource Description Framework), DAM-OIL (DARPA Agent Markup Language), OWL-DL (Web Ontology Language-Description Logics) or Topic Maps)).…”

Section: Graph-based Knowledge Representation and Reasoningmentioning

confidence: 99%

Knowledge-based support in Non-Destructive Testing for health monitoring of aircraft structures

Kamsu-Foguem

2012

Advanced Engineering Informatics

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OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. Maintenance manuals include general methods and procedures for industrial maintenance and they contain information about principles of maintenance methods. Particularly, Non-Destructive Testing (NDT) methods are important for the detection of aeronautical defects and they can be used for various kinds of material and in different environments. Conventional non-destructive evaluation inspections are done at periodic maintenance checks. Usually, the list of tools used in a maintenance program is simply located in the introduction of manuals, without any precision as regards to their characteristics, except for a short description of the manufacturer and tasks in which they are employed. Improving the identification concepts of the maintenance tools is needed to manage the set of equipments and establish a system of equivalence: it is necessary to have a consistent maintenance conceptualization, flexible enough to fit all current equipment, but also all those likely to be added/used in the future. Our contribution is related to the formal specification of the system of functional equivalences that can facilitate the maintenance activities with means to determine whether a tool can be substituted for another by observing their key parameters in the identified characteristics. Reasoning mechanisms of conceptual graphs constitute the baseline elements to measure the fit or unfit between an equipment model and a maintenance activity model. Graph operations are used for processing answers to a query and this graph-based approach to the search method is in-line with the logical view of information retrieval. The methodology described supports knowledge formalization and capitalization of experienced NDT practitioners. As a result, it enables the selection of a NDT technique and outlines its capabilities with acceptable alternatives.

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“…Description logics have been a successful attempt to combine well-defined logical semantics with efficient reasoning, but they suffer the problem of explaining specialization. Furthermore, conceptual graphs can be easily translated into the terminology of some other approaches in knowledge engineering, such as RDF [64], [65].…”

Section: Roles and Uses Of Ontologymentioning

confidence: 99%

Knowledge formalization in experience feedback processes: An ontology-based approach

Foguem

Coudert

Béler

et al. 2008

Computers in Industry

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Because of the current trend of integration and interoperability of industrial systems, their size and complexity continue to grow making it more difficult to analyze, to understand and to solve the problems that happen in their organizations. Continuous improvement methodologies are powerful tools in order to understand and to solve problems, to control the effects of changes and finally to capitalize knowledge about changes and improvements. These tools involve suitably represent knowledge relating to the concerned system. Consequently, Knowledge Management (KM) is an increasingly important source of competitive advantage for organizations. Particularly, the capitalization and sharing of knowledge resulting from experience feedback are elements which play an essential role in the continuous improvement of industrial activities. In this paper, the contribution deals with semantic interoperability and relates to the structuring and the formalization of an Experience Feedback (EF) process aiming at transforming information or understanding gained by experience into explicit knowledge. The reuse of such knowledge has proved to have significant impact on achieving the missions of companies. However, the means of describing the knowledge objects of an experience generally remain informal. Based on an experience feedback process model and conceptual graphs, this paper takes domain ontology as a framework for the clarification of explicit knowledge and know-how, the aim of which is to get lessons learned descriptions that are significant, correct and applicable.

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Automated conversion between different knowledge representation formats

Cited by 27 publications

References 2 publications

Graph-based reasoning in collaborative knowledge management for industrial maintenance

Graph-based reasoning in collaborative knowledge management for industrial maintenance

Knowledge-based support in Non-Destructive Testing for health monitoring of aircraft structures

Knowledge formalization in experience feedback processes: An ontology-based approach

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