| W97-0110 | model is described to achieve | rule optimization | for the information extraction |
| W97-0110 | generalize the third entity . The | rule optimization | process is to automatically control |
| W97-0110 | through a training pro- cess . The | rule optimization | makes it easier for the information |
| W97-0110 | processing new information . This | rule optimization | process will be explained in |
| W97-0110 | Statistical Generalization Tree in | Rule Optimization | * </title> Joyce Yue Chai Alan |
| W97-0110 | question rising here is can we use GT | rule optimization | method to achieve the information |
| W97-0110 | respectively , address training , | rule optimization | , and the scanning of new information |
| P08-1064 | decoding very slow . Thus , effective | rule optimization | and pruning algorithms are highly |
| W97-0110 | specifically describes the automated | rule optimization | method and the usage of WordNet |
| W97-0110 | Future Work This paper describes a | rule optimization | approach by using Generalization |
| W04-0505 | frequent in the negative set . ( 2 ) | Rule optimization | . Instead of Ripper 's rule pruning |
| W97-0809 | rule generalization process , a | rule optimization | engine , based on WordNet , generalizes |
| W97-0110 | requirements from the user , the | Rule Optimization | Engine , based on WordNet , generalizes |
| W97-0110 | the synset at the same level . | Rule Optimization | The specific rule can be generalized |
