P13-1080 in several ways . First , the rule representation itself is adjusted to allow sequences
P07-1074 projections . We propose a novel rule representation enabling the composition of n-ary
P07-1074 for projections . We propose a rule representation that supports this strategy .
C82-1057 control frames which supervise the rule representation frames discussed in Sec . 3.1
N06-1030 geometric trend particular to our rule representation ? And second , is " total number
C82-1057 register . After selection of this rule representation frame control passes to state
P07-1074 relation extraction tasks . The rule representation models for automatic or unsupervised
D12-1012 AQL provides a very expressive rule representation language that is proven to be
J12-4006 modeled with our more elaborate rule representation . that ψ ( root ) is set
C82-1057 to the state specified by the rule representation frame . 3 ) 4 ) If matched rule
P01-1044 performance is dramatically affected by rule representation and tree transformations , but
P07-1074 3 DARE Rule Representation Our rule representation is designed to specify the location
C82-1057 into a state transition network . Rule representation frames and control frames are
D13-1108 ordering . We adopt this kind of rule representation to hold the property of long
C88-1025 ' / EC , we develop a general rule representation form for the representation of
C82-1057 register , and grammatical rules ( rule representation frames and control frames ) .
C82-1057 P ) does not exist and if the rule representation frame does not specify the new
C82-1057 frames and the several types of rule representation frames . These are examples :
C82-1057 determines the name of the next rule representation frame , and stores this name
D09-1108 concept of hyper - tree for compact rule representation and a hyper - tree-based fast
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