Index of papers in Proc. ACL 2010 that mention

**maximum entropy**

Introduction | This is done using a maximum entropy model (call it MAXENT). |

Introduction | Then, the remaining constituents are ordered using a second maximum entropy model (MAXENTZ). |

Introduction | The maximum entropy model for both steps rely on the following features: |

maximum entropy is mentioned in 5 sentences in this paper.

Topics mentioned in this paper:

- coreference (14)
- noun phrases (14)
- word order (11)

Abstract | We use a maximum entropy classifier to predict translation errors by integrating word posterior probability feature and linguistic features. |

Conclusions and Future Work | In this paper, we have presented a maximum entropy based approach to automatically detect errors in translation hypotheses generated by SMT |

Error Detection with a Maximum Entropy Model | For classification, we employ the maximum entropy model (Berger et al., 1996) to predict whether a word 21) is correct or incorrect given its feature vector p. |

Introduction | We integrate two sets of linguistic features into a maximum entropy (MaxEnt) model and develop a MaxEnt-based binary classifier to predict the category (correct or incorrect) for each word in a generated target sentence. |

maximum entropy is mentioned in 4 sentences in this paper.

Topics mentioned in this paper:

- development set (9)
- machine translation (7)
- MaXEnt (7)

Automated Classification | We use a Maximum Entropy (Berger et al., 1996) classifier with a large number of boolean features, some of which are novel (e. g., the inclusion of words from WordNet definitions). |

Automated Classification | Maximum Entropy classifiers have been effective on a variety of NLP problems including preposition sense disambiguation (Ye and Baldwin, 2007), which is somewhat similar to noun compound interpretation. |

Automated Classification | The results for these runs using the Maximum Entropy classifier are presented in Table 4. |

maximum entropy is mentioned in 3 sentences in this paper.

Topics mentioned in this paper:

- Turkers (24)
- semantic relations (7)
- Mechanical Turk (6)