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Knowledge-Driven Wikipedia Article Recommendation for Electronic Textbooks

Part of the Lecture Notes in Computer Science book series (LNISA,volume 12315)


In this paper, we introduce an approach that combines automatic domain knowledge modeling, student modeling, and content recommendation approaches to recommend relevant Wikipedia articles for students working with online electronic textbooks.


  • Recommender systems
  • Personalization
  • Student model
  • Knowledge graph
  • Electronic textbooks
  • Concept extraction

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Correspondence to Behnam Rahdari , Peter Brusilovsky , Khushboo Thaker or Jordan Barria-Pineda .

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Rahdari, B., Brusilovsky, P., Thaker, K., Barria-Pineda, J. (2020). Knowledge-Driven Wikipedia Article Recommendation for Electronic Textbooks. In: Alario-Hoyos, C., Rodríguez-Triana, M.J., Scheffel, M., Arnedillo-Sánchez, I., Dennerlein, S.M. (eds) Addressing Global Challenges and Quality Education. EC-TEL 2020. Lecture Notes in Computer Science(), vol 12315. Springer, Cham.

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-57716-2

  • Online ISBN: 978-3-030-57717-9

  • eBook Packages: Computer ScienceComputer Science (R0)