| S07-1085 | paper describes a supervised , | knowledge-intensive approach | to the automatic identification |
| J09-4010 | 1998 ) . In recent times , such | knowledge-intensive approaches | to content delivery have been |
| P15-1036 | Conclusion We have presented a | knowledge-intensive approach | to prepositional phrase ( PP |
| J10-3003 | and Inui ( 2005 ) take a more | knowledge-intensive approach | to building a Japanese corpus |
| W03-2602 | reliable answer . Unfortunately , | knowledge-intensive approaches | do not scale up well when attempts |
| W03-0415 | accuracy of 28 % . Using a much more | knowledge-intensive approach | , Hahn and Schnattinger ( 1998 |
| P14-2086 | relations , applying a super - vised , | knowledge-intensive approach | . Chklovski and Pantel ( 2004 |
| J05-1002 | text planning that allow a less | knowledge-intensive approach | , GOALGETTER associates every |
| P98-1079 | meanings from context using a | knowledge-intensive approach | . But our work differs from theirs |
