TY - GEN
T1 - Expanding the web of knowledge
T2 - 30th ACM Conference on Hypertext and Social Media, HT 2019
AU - Alpizar-Chacon, Isaac
AU - Sosnovsky, Sergey
N1 - Publisher Copyright:
© 2019 Association for Computing Machinery.
PY - 2019/9/12
Y1 - 2019/9/12
N2 - Textbooks are educational documents created, structured and formatted in a way that facilitates understanding. Most digital textbooks are released as mere digital copies of their printed counterparts. We present a mechanism that extracts knowledge models from textbooks and enriches their content with additional links (both internal and external). The textbooks essentially become hypertext documents where individual pages are annotated with important concepts in the domain. We also show that extracted models can be automatically connected to the Linked Open Data cloud, which helps further facilitate access, discovery, enrichment, and adaptation of textbook content. Integrating multiple textbooks from the same domain increases the coverage of the composite model while keeping its accuracy relatively high. The overall results of the evaluation show that the proposed approach can generate models of good quality and is applicable across multiple domains.
AB - Textbooks are educational documents created, structured and formatted in a way that facilitates understanding. Most digital textbooks are released as mere digital copies of their printed counterparts. We present a mechanism that extracts knowledge models from textbooks and enriches their content with additional links (both internal and external). The textbooks essentially become hypertext documents where individual pages are annotated with important concepts in the domain. We also show that extracted models can be automatically connected to the Linked Open Data cloud, which helps further facilitate access, discovery, enrichment, and adaptation of textbook content. Integrating multiple textbooks from the same domain increases the coverage of the composite model while keeping its accuracy relatively high. The overall results of the evaluation show that the proposed approach can generate models of good quality and is applicable across multiple domains.
KW - DBpedia
KW - Knowledge Extraction
KW - Named Entity Disambiguation
KW - Semantic Linking
KW - Textbook
UR - http://www.scopus.com/inward/record.url?scp=85067814049&partnerID=8YFLogxK
U2 - 10.1145/3342220.3343671
DO - 10.1145/3342220.3343671
M3 - Contribución a la conferencia
AN - SCOPUS:85067814049
T3 - HT 2019 - Proceedings of the 30th ACM Conference on Hypertext and Social Media
SP - 9
EP - 18
BT - HT 2019 - Proceedings of the 30th ACM Conference on Hypertext and Social Media
PB - Association for Computing Machinery, Inc
Y2 - 17 September 2019 through 20 September 2019
ER -