| tech,7-5-J05-1003,bq | introduce a new <term> method </term> for the <term> | reranking task | </term> , based on the <term> boosting approach | #8766 We introduce a new method for the reranking task , based on the boosting approach to ranking problems described in Freund et al. (1998). |
| model,7-7-J05-1003,bq | <term> log-likelihood </term> under a <term> | baseline model | </term> ( that of <term> Collins [ 1999 ] </term> | #8806 The method combined the log-likelihood under a baseline model (that of Collins [1999]) with evidence from an additional 500,000 features over parse trees that were not included in the original model. |
| tech,36-12-J05-1003,bq | ranking tasks </term> , for example , <term> | speech recognition | </term> , <term> machine translation </term> | #8972 Although the experiments in this article are on natural language parsing (NLP), the approach should be applicable to many other NLP problems which are naturally framed as ranking tasks, for example, speech recognition , machine translation, or natural language generation. |
| tech,39-12-J05-1003,bq | , <term> speech recognition </term> , <term> | machine translation | </term> , or <term> natural language generation | #8975 Although the experiments in this article are on natural language parsing (NLP), the approach should be applicable to many other NLP problems which are naturally framed as ranking tasks, for example, speech recognition, machine translation , or natural language generation. |
