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Automatic extraction of Learning Object Metadata (LOM) from HTML web pages

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

It is difficult to locate learning resources on the Internet due to the loose structure of the web. Even with the help of search engines, there are simply too many search results with poor relevancy. In order to solve this problem, learning technology standards such as ADL SCORM, Dublin Core, IMS Specification, IEEE LOM, etc are emerged to provide a standard to identify and describe learning resources. Learning technology standards provide a structured index in describing learning objects and thus, help users in identifying a learning object with higher relevancy. However, the IEEE LOM standard contains too many attributes, making authors reluctant to use the standard. This paper discusses the difficulties of adapting to learning technology standards and describes a framework that automatically extracts important information from HTML web pages and maps them with attributes of the IEEE LOM standard. © 2005 Asia-Pacific Society for Computers in Education.
Original languageEnglish
Title of host publicationProc. Int. Conf. on Computers in Education 2005: "Towards Sustainable and Scalable Educational Innovations Informed by the Learning Sciences"- Sharing Research Results and Exemplary Innovations, ICCE
Pages458-465
Publication statusPublished - 2005
Event13th International Conference on Computers in Education, ICCE 2005 - Singapore, Singapore
Duration: 28 Nov 20052 Dec 2005

Conference

Conference13th International Conference on Computers in Education, ICCE 2005
PlaceSingapore
CitySingapore
Period28/11/052/12/05

Research Keywords

  • Automatic extraction
  • IEEE LOM
  • Learning technology standards

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