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Automated Extraction of Semantic Concepts from Semi-structured Data: Supporting Computer-Based Education through the Analysis of Lecture Notes

  • Thushari Atapattu
  • Katrina Falkner
  • Nickolas Falkner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7446)

Abstract

Computer-based educational approaches provide valuable supplementary support to traditional classrooms. Among these approaches, intelligent learning systems provide automated questions, answers, feedback, and the recommendation of further resources. The most difficult task in intelligent system formation is the modelling of domain knowledge, which is traditionally undertaken manually or semi-automatically by knowledge engineers and domain experts. However, this error-prone process is time-consuming and the benefits are confined to an individual discipline. In this paper, we propose an automated solution using lecture notes as our knowledge source to utilise across disciplines. We combine ontology learning and natural language processing techniques to extract concepts and relationships to produce the knowledge representation. We evaluate this approach by comparing the machine-generated vocabularies to terms rated by domain experts, and show a measurable improvement over existing techniques.

Keywords

ontology POS tagging lecture notes concept extraction 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Thushari Atapattu
    • 1
  • Katrina Falkner
    • 1
  • Nickolas Falkner
    • 1
  1. 1.School of Computer ScienceUniversity of AdelaideAdelaideAustralia

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