SGER: Data-Driven Linguistic Ontology Development

在国家科学基金会的支持下，William刘易斯博士将领导一个团队进行为期18个月的语言本体开发和文本挖掘研究。在Scott Farrar博士的帮助下，该项目将通过对网络上存在的语言数据结构进行广泛的文本挖掘来扩展现有的语言本体，特别关注主要在学术文章中发现的行间文本。文本挖掘任务的核心是开发一套用于访问和部署本体的编程工具。本体论将指导文本挖掘对Web上的数据进行解释，文本挖掘将循环地用于开发本体论。随着越来越多的语言数据被放置在Web上，对这些数据资源的定位、访问和比较的需求已成为该学科的基本要求。不幸的是，由于不同研究人员使用的术语不同，资源的获取可能有限或困难，并且通常不可能进行跨资源的比较。语言本体表示一种将该领域的知识空间编码为计算工件的方式，该计算工件使得资源的自动比较成为可能，而不管这些资源被编码的术语。语言资源的文本挖掘是所提出的研究的一个重要部分，因为它可以允许开发语言知识的全面画面，并且当应用于本体构建时，可以用于使本体更具“数据感知”。此外，开发访问本体的编程工具将有额外的好处，使本体更容易被其他希望使用它的研究人员访问，为语言学语义网奠定基础。

With National Science Foundation support, Dr. William Lewis will lead a team conducting eighteen months of research on linguistic ontology development and text mining. The project, with the help of Dr. Scott Farrar, will expand an existing linguistic ontology through extensive text mining of linguistic data structures that exist on the Web, focusing specifically on interlinear text found mostly in scholarly articles. Central to the text mining task will be the development of a set of programming tools for accessing and deploying the ontology. The ontology will guide the text mining in interpreting the data found on the Web, and the text mining will be used cyclically to develop the ontology.As more and more linguistic data has been placed on the Web, the need for locating, accessing, and comparing these data resources has become essential to the discipline. Unfortunately, because the terminology used by various researchers differs, access to resources can be limited or difficult, and comparison across resources is generally not possible. A linguistic ontology represents a way of encoding the knowledge space of the field as a computational artifact that makes possible the automated comparison of resources, irrespective of the terminology in which these resources are encoded. Text mining of linguistic resources is an essential part of the proposed research, because it can allow a comprehensive picture of linguistic knowledge to develop, and when applied to ontology construction, can be used to make the ontology more "data-aware." Further, the development of programming tools to access the ontology will have the added benefit of making the ontology more readily accessible to other researchers wishing to use it, laying the foundations for a Semantic Web for linguistics.