| D09-1113 | pairs compared with sequential | supervised learning approach | . The quality of click pairs |
| D09-1071 | tasks are commonly tackled using | supervised learning approaches | . These learning methods rely |
| D14-1147 | Sun et al. ( 2008 ) proposed a | supervised learning approach | by using SVM model . Tsuruoka |
| E12-1023 | first experiment , we compare our | supervised learning approach | to the hand-tuned ap - proach |
| C02-1088 | application . The second belongs to a | supervised learning approach | , which employs a statistical |
| D11-1144 | Bootstrapping for Dictionary Expansion The | supervised learning approach | assumes the existence of an annotated |
| E14-3008 | easily exploit the annotation for a | supervised learning approach | ( see Section 5 ) . 3 Related |
| E12-1023 | Abstract In this paper , we present a | supervised learning approach | to training submodu - lar scoring |
| D14-1084 | 2007 ) are the first to employ a | supervised learning approach | to Chinese ZP resolution . They |
| D11-1120 | directly useful when we wish to apply | supervised learning approaches | to classify tweets for these |
| D10-1010 | . 8 Conclusion We presented a | supervised learning approach | to the question ranking task |
| D13-1067 | mary . ➢ MaxEnt : as a | supervised learning approach | , maximum entropy uses textual |
| D10-1031 | guaranteed . 6 Approach We propose a | supervised learning approach | , where instances are positive |
| E09-1031 | tagging ( Brill , 1995 ) . TBL is a | supervised learning approach | , since it relies on gold-annotated |
| D11-1074 | However , most existing work uses | supervised learning approaches | that require careful feature |
| E12-1023 | Conclusions This paper presented a | supervised learning approach | to extractive document summarization |
| D10-1079 | well as base - forms . It is a | supervised learning approach | that requires data labeled with |
| D13-1146 | by Mikheev ( 2002 ) . Existing | supervised learning approaches | for sentence boundary detection |
| D08-1068 | . 2 Related Work Most existing | supervised learning approaches | for coreference resolution are |
| E09-3007 | recogniser , following the classical | supervised learning approach | with a top performer out of more |
