Concept hierarchy extraction from textbooks

Shuting Wang, Chen Liang, Zhaohui Wu, Kyle Williams, Bart Pursel, Benjamin Brautigam, Sherwyn Saul, Hannah Williams, Kyle Bowen, C. Lee Giles

Research output: Chapter in Book/Report/Conference proceedingConference contribution

42 Scopus citations


Concept hierarchies have been useful tools for presenting and organizing knowledge. With the rapid growth of online knowledge resources, automatic concept hierarchy extraction is increasingly attractive. Here, we focus on concept extraction from textbooks based on the knowledge in Wikipedia. Given a book, we extract important concepts in each book chapter using Wikipedia as a resource and from this construct a concept hierarchy for that book. We define local and global features that capture both the local relatedness and global coherence embedded in that textbook. In order to evaluate the proposed features and extracted concept hierarchies, we manually construct concept hierarchies for three well used textbooks by labeling important concepts for each book chapter. Experiments show that our proposed local and global features achieve better performance than using only keyphrases to construct the concept hierarchies. Moreover, we observe that incorporating global features can improve the concept ranking precision and reaffirms the global coherence in the book.

Original languageEnglish (US)
Title of host publicationDocEng 2015 - Proceedings of the 2015 ACM Symposium on Document Engineering
PublisherAssociation for Computing Machinery, Inc
Number of pages10
ISBN (Electronic)9781450333078
StatePublished - Sep 8 2015
EventACM Symposium on Document Engineering, DocEng 2015 - Lausanne, Switzerland
Duration: Sep 8 2015Sep 11 2015

Publication series

NameDocEng 2015 - Proceedings of the 2015 ACM Symposium on Document Engineering


OtherACM Symposium on Document Engineering, DocEng 2015

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Software


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