基于多种规则的课程元数据自动抽取

A Rule-based Metadata Extractor for Learning Materials

在线课程组织和管理系统就是为了使学习更加便利而提供的一个教育资源的集成平台。作为系统中重要环节的元数据抽取模块,需要对半结构化网页能够达到较好的抽取精确性,并具有处理结构松散文档的能力。本文设计并实现了一种按照指定规则自动抽取的元数据方法。该方法能够按照多优先级规则匹配网页元数据,并按照两步抽取的方法进行精细化处理。针对不同的问题域使用不同规则抽取,不需对程序进行特定修改。实验证明,这种方法能够很好地处理半结构化网页,F测度达到85%以上,具有较好的实用价值。

Integrating all kinds of learning material is becoming more and more significant for the teachers and students to take advantage of the online E-learning courses. As the key part of the whole Online Course Organization System,Metadata Extraction function needs to heaccurate enough when dealing with semi-structured documents, even those incompact ones. We design and !mplement a Metadata Extractor to .compare. between several rules ordered by priority,and there is another step of information refinement to help improving the final accuracy. When domain changes, users just need to input.specific rules, without considering the program. The experiment, shows that our new method can perform very well withthose semi-structured documents, with F measure higher than 85%, which indicates that this method is quite feasible in reality.