| 基于多分类器决策的词义消歧方法 |
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| 引用本文： | 全昌勤,何婷婷,姬东鸿,余绍文.基于多分类器决策的词义消歧方法[J].计算机研究与发展,2006,43(5):933-939. |
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| 作者姓名： | 全昌勤 何婷婷 姬东鸿 余绍文 |
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| 作者单位： | 1. 华中师范大学计算机科学与技术系,武汉,430079
2. 长江大学计算机科学学院,沙市,434025 |
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| 基金项目： | 中国科学院资助项目;科技部科研项目;教育部科学技术研究项目 |
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| 摘 要： | 词义消歧问题可以形式化为典型的分类问题.通过学习少量带有词义标注的语料构造多个消歧分量分类器,并利用未标语料动态地对这些分类器进行更新,根据最终分量分类器分别对多义词义项的判定结果,组合决策多义词的义项.该方法无需手工构造大规模具有词义标注的语料库,并且具有较高的消歧准确率.
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| 关 键 词： | 自然语言处理 词义消歧 分量分类器 |
| 收稿时间： | 05 11 2005 12:00AM |
| 修稿时间： | 2005-05-112005-09-26 |
Word Sense Disambiguation Based on Multi-Classifier Decision |
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| Quan Changqin,He Tingting,Ji Donghong,Yu Shaowen.Word Sense Disambiguation Based on Multi-Classifier Decision[J].Journal of Computer Research and Development,2006,43(5):933-939. |
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| Authors: | Quan Changqin He Tingting Ji Donghong Yu Shaowen |
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| Affiliation: | 1.Department of Computer Science and Technology, Central China Normal University, Wuhan 430079;2.Computer Science College of Yangtze University, Shashi 434025 |
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| Abstract: | The problem of word sense disambiguation can be formalized to be a typical classify problem. The committee classifiers are trained by learning a small set of labeled examples, and then these classifiers are updated dynamically by unlabeled examples. The senses of ambiguous words are determined by combining the decision of the final committee classifiers. This approach avoids constructing large-scale sense-tagged corpus, and has higher accurate rate. |
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| Keywords: | AdaBoost |
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