Conversion of Learning Objects to Meaningful XML

Y. Biletskiy and T. Scribner (Canada)


Distance Education, Information Retrieval, XML, e-Learning


This paper presents an approach of information extraction from HTML documents which represent learning objects and converting them into meaningful XML format, which represents not only the document’s content but also the meaning of its data entries. The present paper covers a very specific domain of course descriptions because the work is closely related to the research in achieving interoperability among semantically heterogeneous learning objects and learners [1]. Once the meaningful XML representation of a learning object is built the document can be converted to any other format as well as to any learner’s context. The extraction methods presented in this work use recognition of a finite number of patterns in the course descriptions. These methods are implemented in the HTML-XML Converter, and an example of the conversion process is given.

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