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2016 IEEE/WIC/ACM International Conference on Web Intelligence (WI) (2016)
Omaha, NE, USA
Oct. 13, 2016 to Oct. 16, 2016
ISBN: 978-1-5090-4470-2
pp: 18-25
ABSTRACT
Although the volume of online educational resources has dramatically increased in recent years, many of these resources are isolated and distributed in diverse websites and databases. This hinders the discovery and overall usage of online educational resources. By using linking between related subsections of online textbooks as a testbed, this paper explores multiple knowledge-based content linking algorithms for connecting online educational resources. We focus on examining semantic-based methods for identifying important knowledge components in textbooks and their usefulness in linking book subsections. To overcome the data sparsity in representing textbook content, we evaluated the utility of external corpuses, such as more textbooks or other online educational resources in the same domain. Our results show that semantic modeling can be integrated with a term-based approach for additional performance improvement, and that using extra textbooks significantly benefits semantic modeling. Similar results are obtained when we applied the same approach to other domains.
INDEX TERMS
Joining processes, Semantics, Information retrieval, Knowledge based systems, Adaptation models, Context, Standards
CITATION

R. Meng, S. Han, Y. Huang, D. He and P. Brusilovsky, "Knowledge-Based Content Linking for Online Textbooks," 2016 IEEE/WIC/ACM International Conference on Web Intelligence (WI), Omaha, NE, USA, 2016, pp. 18-25.
doi:10.1109/WI.2016.0014
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