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Record Nr. |
UNINA9910346889003321 |
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Autore |
Zhang Melvyn W. B |
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Titolo |
Get Through MRCPsych Paper A : Mock Examination Papers, Two Volume Set |
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Pubbl/distr/stampa |
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Milton : , : Taylor & Francis Group, , 2017 |
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©2017 |
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ISBN |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 electronic resource (XVI, 331 p. p.) |
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Altri autori (Persone) |
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HoCyrus S. H |
HoRoger |
TreasadenIan H |
PuriBasant |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Sommario/riassunto |
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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. |
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