| 基于维基百科的自动词义消歧方法 |
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| 引用本文： | 史天艺,李明禄.基于维基百科的自动词义消歧方法[J].计算机工程,2009,35(18):62-65. |
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| 作者姓名： | 史天艺 李明禄 |
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| 作者单位： | 上海交通大学计算机科学与工程系,上海,200240 |
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| 基金项目： | 国家"863"计划基金资助项目 |
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| 摘 要： | 针对传统词义消歧仅基于上下文语境而导致准确率低的问题，提出一种多策略的无监督自动词义消歧方法。利用从维基百科在线中提炼出的丰富语义知识，线性融合上下文语境、背景知识和语义信息3大特征，根据逻辑回归算法学习各特征的权重，选取最大融合值所对应的候选项作为最优词义。在SENSEVAL数据集上取得了85．50％的平均准确率，验证了该方法的有效性。
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| 关 键 词： | 词义消歧 维基百科 知识库 无监督学习 |
| 修稿时间： | |
Automatic Word Sense Disambiguation Method Based on Wikipedia |
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| SHI Tian-yi,LI Ming-lu.Automatic Word Sense Disambiguation Method Based on Wikipedia[J].Computer Engineering,2009,35(18):62-65. |
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| Authors: | SHI Tian-yi LI Ming-lu |
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| Affiliation: | Department of Computer Science & Engineering;Shanghai Jiaotong University;Shanghai 200240 |
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| Abstract: | Most traditional Word Sense Disambiguation(WSD) method is just based on contextual information, often results in inaccurate output.A multi-level unsupervised automatic WSD method which works efficiently is promoted.This method utilizes the rich semantic information extracted from online Wikipedia, makes a linear fusion of contextual information, background knowledge and semantic information, uses logistic regression algorithm to learn the weight of each feature, and selects the one with the maximum combined... |
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| Keywords: | Word Sense Disambiguation(WSD) Wikipedia knowledge base unsupervised learning |
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