Automatic Verbalisation of SNOMED Classes Using OntoVerbal

Liang, Shao Fen; Stevens, Robert; Scott, Donia; Rector, Alan L.

doi:10.1007/978-3-642-22218-4_43

Cited by 10 publications

(14 citation statements)

References 3 publications

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“…We propose the fourth trend to cope with this limitation. For example, this trend requires methods of verbalisation (transformation into natural language text) or illustration (transformation into images) of controlled terminologies [76,77]. Adequate software applications are needed to further support domain experts in their analyses and to properly interpret their feedback by modifying the out-dated terminologies in an automatic and safe manner.…”

Section: Trends and Open Challengesmentioning

confidence: 99%

Management of Dynamic Biomedical Terminologies: Current Status and Future Challenges

Silveira

Reis²,

Pruski³

2015

Yearb Med Inform

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SummaryObjectives: Controlled terminologies and their dependent artefacts provide a consensual understanding of a domain while reducing ambiguities and enabling reasoning. However, the evolution of a domain's knowledge directly impacts these terminologies and generates inconsistencies in the underlying biomedical information systems. In this article, we review existing work addressing the dynamic aspect of terminologies as well as their effects on mappings and semantic annotations. Methods: We investigate approaches related to the identification, characterization and propagation of changes in terminologies, mappings and semantic annotations including techniques to update their content. Results and conclusion: Based on the explored issues and existing methods, we outline open research challenges requiring investigation in the near future.

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Section: Trends and Open Challengesmentioning

confidence: 99%

Management of Dynamic Biomedical Terminologies: Current Status and Future Challenges

Silveira

Reis²,

Pruski³

2015

Yearb Med Inform

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“…[79,80]), or generating a summarized report of an ontology (e.g. [81]). The requirements in the SRS document coming from the avionics case study were well-structured.…”

Section: Evaluation Of the Ontology Correctnessmentioning

confidence: 99%

Ontology-based Software Test Case Generation (OSTAG)

Tarasov

Tan

Adlemo

et al. 2015

European Projects in Knowledge Applications and Intelligent Systems

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Testing is a paramount quality assurance activity in every software development project, especially for embedded, safety critical systems. During the test process, a lot of effort is put into the generation of test cases. The presented OSTAG project aimed at developing methods and techniques to automate the software test case generation for black-box testing. The proposed approach was based on the creation of a software requirements ontology and the application of inference rules on the ontology to derive test cases. The ontology represents knowledge of the requirements, the software system and the corresponding application domain while the inference rules formalize knowledge from documents and experienced testers in the domain of test planning and test case generation. A software prototype of the approach was implemented and one of the industrial project partners evaluated the results. An alternative method for generating test cases, based on genetic algorithms, was also explored.

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“…For example, ACE View (Fuchs et al, 2008) (a Protégé extension) presents an "entailments view" showing class assertions, property assertions and subclass axioms where the involved individuals, properties, and classes are always named. OntoVerbal (Liang et al, 2011) (a Protégé plugin) concentrates on axiom realisation, grouping and aggregation, and does not present any approach to tackle axiom selection. The RoundTrip Ontology Authoring (ROA) (Davis et al, 2008) environment only presents axioms that have been explicitly defined, selecting in turn top level classes, subclasses, instances, class properties and their respective domain and ranges, and instance properties.…”

Section: Approaches Using Syntaxmentioning

confidence: 99%