7 IR models based on predicate logic
7 IR models based on predicate logic
7 IR models based on predicate logic
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<str<strong>on</strong>g>IR</str<strong>on</strong>g> <str<strong>on</strong>g>models</str<strong>on</strong>g> <str<strong>on</strong>g>based</str<strong>on</strong>g> <strong>on</strong> <strong>predicate</strong> <strong>logic</strong> 31<br />
Disjoint events<br />
example: imprecise attribute values<br />
# py(dk,av).<br />
0.2 py(d3,89).<br />
0.7 py(d3,90).<br />
0.1 py(d3,91).<br />
interpretati<strong>on</strong>:<br />
P (W 1 ) = 0.2: {py(d3,89)}<br />
P (W 2 ) = 0.7: {py(d3,90)}<br />
P (W 3 ) = 0.1: {py(d3,91)}<br />
?- py(X,Y) & Y > 89.<br />
d3 [p(d3,90) | p(d3,91)] 0.7 + 0.1 = 0.8<br />
Norbert Fuhr
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