02044nam 22005293 450 991034688900332120240508084503.01-000-03150-0(CKB)4920000000101632(oapen)https://directory.doabooks.org/handle/20.500.12854/55250(MiAaPQ)EBC31149702(Au-PeEL)EBL31149702(EXLCZ)99492000000010163220240508d2017 uy 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierGet Through MRCPsych Paper A Mock Examination Papers, Two Volume Set1st ed.Milton :Taylor & Francis Group,2017.©2017.1 electronic resource (XVI, 331 p. p.)1-4987-9628-1 3-86644-958-5 According to the Semantic Web a formal representation of knowledge is described by an ontology. This formal representation enables a unique identification of elements within an ontology. By the use of natural language for element annotation, ambiguity occurs and a unique element identification based on natural language cannot be guaranteed. This book describes an approach to identify the most relevant element described by a natural language term by reducing the aspect of ambiguity to a minimum.Semantic WebSpreading ActivationSemantic WebWord-sense disambiguationMehrdeutigkeitGraphentheorieDisambiguierungGraph theorySpreading ActivationZhang Melvyn W. B1737480Ho Cyrus S. H1737481Ho Roger1737482Treasaden Ian H1737483Puri Basant1737484MiAaPQMiAaPQMiAaPQBOOK9910346889003321Get Through MRCPsych Paper A4159425UNINA