W01-0807 be achieved by making use of a rule generalization hierarchy . Then , the statements
P13-2069 address the above issues with rule generalization , then consider all the permutations
P07-1105 . Similarly , the goal of the rule generalization step is to obtain a new target
D11-1020 categories . Figure 5 illustrates the rule generalization process under these restrictions
W97-0110 user 's needs . In this way , rule generalization makes the customization for a
W97-0809 processing new information . This rule generalization process will be described in
A97-2004 articles from the domain . The Rule Generalization routines , with the help of WordNet
P11-1003 baseline system . 1 Introduction Rule generalization remains a key challenge for current
W97-0117 independence can be introduced through rule generalization . Furth research and evaluations
W97-0809 respectively , address training , rule generalization , and the scanning of new information
P07-1105 generalized from a grammar , using the rule generalization step . In Figure 2 , the grammar
W00-1436 background and the procedure of rule generalization is described in detail in ( Wanner
J91-2002 distance of ± 5 . Example rule generalization session with the computer system
W97-0809 paper describes the automated rule generalization method and the usage of WordNet
P07-1105 grammars specialized from . The only rule generalization steps allowed in the grammar
C02-1080 within the entities , and performed rule generalization using POS ( part-of-speech )
W97-0110 op - erations : rule creation , rule generalization and rule ap - plication . Rule
A97-2004 system : the Training Process , Rule Generalization , and the Scanning Pro- cess
I05-2033 et al. , 2003 ) used a di erent rule generalization method called RGLearn . Row 4
W07-0731 Data-Oriented Parsing inspired rule generalization technique proposed by Chiang
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