SGER: Data-Driven Linguistic Ontology Development

在国家科学基金会的支持下，威廉·刘易斯博士将带领一个团队进行为期18个月的语言本体开发和文本挖掘研究。该项目在Scott Farrar博士的帮助下，将通过对Web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，特别是专注于主要在学术文章中发现的行间文本。文本挖掘任务的中心将是开发一套用于访问和部署本体的编程工具。本体将指导文本挖掘对Web上的数据进行解释，而文本挖掘将被循环使用来开发本体。随着越来越多的语言数据被放置在Web上，定位、访问和比较这些数据资源的需求成为了这门学科的关键。不幸的是，由于不同研究人员使用的术语不同，获取资源的机会可能有限或困难，而且通常不可能跨资源进行比较。语言本体论代表了一种将领域的知识空间编码为计算人工产物的方式，使得资源的自动比较成为可能，而不管这些资源是用什么术语编码的。语言资源的文本挖掘是本研究的重要组成部分，因为它可以让语言知识的全貌得到发展，并且当应用于本体构建时，可以用来使本体更具数据意识。此外，开发访问本体的编程工具将具有额外的好处，使希望使用本体的其他研究人员更容易访问它，为语言学的语义网奠定基础。

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.