| 基于最大熵的句内时间关系识别 |
| |
| 引用本文： | 王风娥,谭红叶,钱揖丽. 基于最大熵的句内时间关系识别[J]. 计算机工程, 2012, 38(4): 37-39 |
| |
| 作者姓名： | 王风娥 谭红叶 钱揖丽 |
| |
| 作者单位： | 山西大学计算机与信息技术学院,太原,030006 |
| |
| 基金项目： | 国家自然科学基金资助项目（61100138,61005053）;山西省高校科技开发基金资助项目（20091001）;山西省自然科学基金资助项目（2011011016-2） |
| |
| 摘 要： | 分别对句内事件-时间对关系以及事件对之间的时间关系识别进行研究。分析影响时间关系识别的语言特征，如时间关系对之间的依存关系序列、间隔词数、信号词及其位置等，并使用基于最大熵的方法进行识别。实验结果表明，运用该方法获得的事件-时间对关系识别准确率为87.83%，事件对之间的时间关系识别准确率为80.79%。
|
| 关 键 词： | 时间关系 句内时间关系 最大熵 依存分析 自然语言处理 |
| 收稿时间： | 2011-08-17 |
Recognition of Temporal Relation in One Sentence Based on Maximum Entropy |
| |
| WANG Feng-e , TAN Hong-ye , QIAN Yi-li. Recognition of Temporal Relation in One Sentence Based on Maximum Entropy[J]. Computer Engineering, 2012, 38(4): 37-39 |
| |
| Authors: | WANG Feng-e TAN Hong-ye QIAN Yi-li |
| |
| Affiliation: | (School of Computer and Information Technology, Shanxi University, Taiyuan 030006, China) |
| |
| Abstract: | This article studies the recognition of the temporal relation between an event and a time expression and the temporal relation between two events where one event syntactically dominates the other event in one sentence. It analyzes some effective linguistic features such as dependency parsing information, relative positions, signal words, position of signal words and so on. A method based on maximum entropy model is proposed. In addition, how linguistic features could affect temporal relation recognition is analyzed. Experimental results show the accuracies of the two tasks are respectively 87.83% and 80.79%. |
| |
| Keywords: | temporal relation temporal relation in one sentence maximum entropy dependency analysis natural language processing |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
| 点击此处可从《计算机工程》浏览原始摘要信息 |
|
点击此处可从《计算机工程》下载免费的PDF全文 |
