水稻本体实例构建研究

Research on Construction of Rice Ontology Instance

实例是本体的重要组成部分，它在很大程度上决定了本体的可用性。而目前本体实例构建的难度甚至超过了本体构建本身，大多实例的获取、更新和扩充依靠人工完成，既花费大量时间，又难以保证质量。文章在已完成的水稻本体概念框架基础上，利用神经网络方法进行半自动水稻实例抽取，提出水稻本体实例构建框架。统计数据表明，该方法能够有效地提高本体实例构建效率，大幅度降低手工劳动水平，提高本体实例质量，为本体实例构建和本体走向实际应用提供了思路和方法。

Instance is an important component of Ontology, which largely determines the availability of Ontology. Constructing an Ontology Instance is more difficult than Ontology construction itself in many cases. Instance acquiring, updating and expanding rely on manual operation completely. The work needs a lot of time and is hard to ensure quality. Based on the conceptual framework of Ontology, a semi-automatic extraction approach was applied by using neural network （NN） method in rice instances. The construction framework of rice ontology instance was proposed. The result shows that this approach effectively improved the efficiency of Ontology instance construction, significantly reduced the manual labor, and improved the quality of Ontology Instances. This approach provides a new idea and method for Ontology applications from Ontology Instance construction and Ontology.