Theoretical analysis reveals semantic counterparts to Shannon source and channel coding theorems in communication models, suggesting viable frameworks for meaning-preserving data transmission.
This paper studies methods of quantitatively measuring semantic information in communication. We review existing work on quantifying semantic information, then investigate a model-theoretical approach for semantic data compression and reliable semantic communication. We relate our approach to the statistical measurement of information by Shannon, and show that Shannon's source and channel coding theorems have semantic counterparts.
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Bao et al. (2011) studied this question.
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