Semantic Communication

Semantic Information Calculator

In communication, the contents exchanged are not just boring bits, but bits with meanings. How to measure the amount of meaning (knowledge, or semantics) carried by a message? This demo shows a semantic information measure for messages composed using propositional logic sentences.

Enter a propositional expression into the textbox below. The "knowledge entropy" of the expression will be displayed.

Message (Propositional Sentence)
(syntax help)
Likelihood of terms (optional, default values are 0.5)


Information Amount

Knowledge entropy (semantic):1.807 bits
Logical Probability
0.2857
Shannon entropy (syntatic):121.900 bits.

Model Details: (Show/Hide)

    EXP := (WEEKEND OR SATURDAY) AND (SATURDAY IMPLIES WEEKEND)
    SATURDAYWEEKENDEXPProbability
    FALSEFALSEFALSE0.6122
    TRUEFALSEFALSE0.1020
    FALSETRUETRUE0.2449
    TRUETRUETRUE0.0408
    Entropy of models = 1.455 bits
Syntax Help:
TRUE"1"FALSE "0"NOT "!"AND "&"
NAND "!&"OR "|"NOR "!|"XOR "<!>"
IMPLIES"->"NOT_IMPLIES "-!>"IMPLIED_BY"<-"NOT_IMPLIED_BY "<!-"
IFF "<->"

Examples: