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延伸的本体诠释商业新闻

Extending Ontologies for Annotating Business News
课程网址: http://videolectures.net/sikdd08_novalija_eo/  
主讲教师: Inna Novalija
开课单位: 约瑟夫·斯特凡学院
开课时间: 2008-11-07
课程语种: 英语
中文简介:
本体通常用于注释文本数据，主要基于人类语言技术[1]。本研究以人工扩展本体来支援商业新闻的注解。实验在一个著名的Cyc本体上进行，并在两个商业新闻数据集上使用Cyc注释器。我们证明了本体论的扩展导致注释具有更好的与业务领域相关的术语覆盖率。利用原有的Cyc本体对商业新闻中的财务术语进行识别，结果表明，路透社和雅虎财经新闻中的财务术语识别平均精度分别为56%和41%，雅虎财经新闻中的财务术语识别平均精度分别为69%和57%。使用性能提高的扩展结果，雅虎财经新闻的平均精度为82%，平均召回率为73%，路透社新闻的平均精度为84%，平均召回率为63%。
课程简介: Ontologies are commonly used for annotating textual data mainly based on human language technologies [1]. This research focuses on manual extensions of ontologies to support the annotation of business news. Experiments were conducted on a well known Cyc ontology and using Cyc annotator on two business news datasets. We show that the proposed extensions of ontology results in annotation with better coverage of terms that are relevant for the business domain. The results of identifying financial terms in business news using the original Cyc ontology show the average precision of 56% and recall of 41% in case of Reuters news and the average precision of 69% and the recall of 57% in case of Yahoo financial news. Using the proposed extension results with increased performance, the average precision of 82% and average recall of 73% for Yahoo financial news and average precision of 84% and average recall of 63% for Reuters news.
关 键 词: 本体; 文本数据; 语言技术
课程来源: 视频讲座网
最后编审: 2020-07-23：yumf
阅读次数: 41

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