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Knowledge models from PDF textbooks

  • Isaac Alpizar-Chacon
  • , Sergey Sosnovsky

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

Textbooks are educational documents created, structured and formatted by domain experts with the primary purpose to explain the knowledge in the domain to a novice. Authors use their understanding of the domain when structuring and formatting the content of a textbook to facilitate this explanation. As a result, the formatting and structural elements of textbooks carry the elements of domain knowledge implicitly encoded by their authors. Our paper presents an extensible approach towards automated extraction of knowledge models from textbooks and enrichment of their content with additional links (both internal and external). The textbooks themselves essentially become hypertext documents where individual pages are annotated with important concepts in the domain. The evaluation experiments examine several aspects and stages of the approach, including the accuracy of model extraction, the pragmatic quality of extracted models using one of their possible applications— semantic linking of textbooks in the same domain, the accuracy of linking models to external knowledge sources and the effect of integration of multiple textbooks from the same domain. The results indicate high accuracy of model extraction on symbolic, syntactic and structural levels across textbooks and domains, and demonstrate the added value of the extracted models on the semantic level.

Original languageEnglish
Pages (from-to)128-176
Number of pages49
JournalNew Review of Hypermedia and Multimedia
Volume27
Issue number1-2
DOIs
StatePublished - 2021

Keywords

  • DBpedia
  • knowledge modelling
  • model extraction
  • named entity disambiguation
  • PDF processing
  • semantic linking
  • Textbook

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