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| 事件超图模型及类型识别 | |
| 引用本文： | 肖升,何炎祥. 事件超图模型及类型识别[J]. 中文信息学报, 2013, 27(1): 30-39 |
| 作者姓名： | 肖升 何炎祥 |
| 作者单位： | 1. 武汉大学 计算机学院,湖北 武汉 430072; 2. 湖南第一师范学院 信息科学与工程系,湖南 长沙 410205 |
| 基金项目： | 国家自然科学基金资助项目，湖南省教育厅科学研究项目，湖南省高校科技创新团队支持计划资助，湖南省科技厅高新计划资助项目 |
| 摘 要： | 为避免向量空间模型的独立性假设影响事件类型识别,该文提出了一种基于超图的事件类型识别方法。该方法首先用事件超图描写事件元素间的多元有序关系;然后用事件超图模型(由事件超图添加类型组件和层面组件后构成)描述某个(某类)事件在不同观测层面的属性及其结构;最后根据事件的属性及其结构计算其相似度,并借此完成事件类型识别。实验结果显示,此方法识别效率的平均F值达到83.0%,与基于向量空间模型的支持向量机方法和最大熵方法相比,此方法也具有一定优势。 |
| 关 键 词： | 事件抽取 事件类型识别 超图 有向超图 事件超图模型 事件相似度 |
Event Hypergraph Model and Event Type Recognition |
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| XIAO Sheng , HE Yanxiang. Event Hypergraph Model and Event Type Recognition[J]. Journal of Chinese Information Processing, 2013, 27(1): 30-39 | |
| Authors: | XIAO Sheng HE Yanxiang |
| Affiliation: | 1. School of Computer Science, Wuhan University, Wuhan, Hubei 430072, China; 2. Department of Information Science and Engineering, Hunan First Normal College, Changsha, Hunan 410205,China |
| Abstract: | This paper develops an event type recognition approach based on hypergraph to avoid the impact of independence assumption in vector space model.The approach firstly represents the Multi-ordering relationship among event elements by an event hypergraph. Then the approach displays the attribute and its structure of one ( series of) event(s) in various dimensions by the event hypergraph model integrated by the type component and dimension component. Lastly the approach computes the event similarity by the attribute and its structure. The experimental results showed that this approach can increase the efficiency of recognition to 83.0%(F-score), which is better than SVM or ME based on vector space model. Key wordsevent extraction; event type recognition; hypergraph; directed hypergraph; event hypergraph model; event similarity |
| Keywords: | event extraction event type recognition hypergraph directed hypergraph event hypergraph model event similarity |
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