W11-0107 variety of abduction called " weighted abduction " for interpreting natural language
W11-0107 . Section 3 then describes how weighted abduction can be implemented in Markov
W11-0107 abductive proof . Specifically , weighted abduction has the following features :
W02-0211 realizing abductive reasoning . With weighted abduction there is a cost associated with
W11-0107 -RSB- . In this paper we show how weighted abduction can be implemented in Markov
P97-1018 numbers and rules by means of weighted abduction . However , the theories differ
E97-1018 numbers and rules by means of weighted abduction . However , the theories differ
J13-4001 to implement a system based on weighted abduction , I thought the goal was ten
J13-4001 He described his algorithm for weighted abduction . It struck me immediately as
W11-0107 natural language processing , is weighted abduction , which uses logical formulas
W11-0107 published examples of the use of weighted abduction in natural language understanding
N06-1006 that even approaches relying on weighted abduction may be seen in this light . )
P92-1001 points are rel - evant . First , weighted abduction , as a system of inference ,
W11-0107 two significant problems with weighted abduction as it was originally presented
W11-0107 sound probabilistic semantics for weighted abduction . Application to a series of
P98-1052 Hobbs , 1997 ) uses a form of weighted abduction as the reasoning mechanism (
P94-1031 operations can be controlled by " weighted abduction " -LSB- 5 -RSB- , default inheritance
W11-0107 propose an approach that implements weighted abduction in Markov logic , which uses
W11-0107 inference . The second problem with weighted abduction was that the weights and costs
W01-1201 unification of sentence parses , weighted abduction score , etc. ) . The answer candidates
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