%0 Conference Paper %1 Alpizar_Chacon_2019 %A Alpizar-Chacon, Isaac %A Sosnovsky, Sergey %B Proceedings of the 30th ACM Conference on Hypertext and Social Media %D 2019 %I ACM %K electronic-textbook %P 9-18 %R 10.1145/3342220.3343671 %T Expanding the Web of Knowledge %U https://doi.org/10.1145%2F3342220.3343671 %X 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.

@inproceedings{Alpizar_Chacon_2019, abstract = {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. }, added-at = {2020-10-01T17:29:57.000+0200}, author = {Alpizar-Chacon, Isaac and Sosnovsky, Sergey}, biburl = {https://www.bibsonomy.org/bibtex/2df0b58e246c58d4d6988c87333f0a3a9/brusilovsky}, booktitle = {Proceedings of the 30th {ACM} Conference on Hypertext and Social Media}, description = {Expanding the Web of Knowledge | Proceedings of the 30th ACM Conference on Hypertext and Social Media}, doi = {10.1145/3342220.3343671}, interhash = {aa5c6cd8f752f0824c72721c84caf904}, intrahash = {df0b58e246c58d4d6988c87333f0a3a9}, keywords = {electronic-textbook}, month = sep, pages = {9-18}, publisher = {{ACM}}, timestamp = {2020-10-01T17:29:57.000+0200}, title = {Expanding the Web of Knowledge}, url = {https://doi.org/10.1145%2F3342220.3343671}, year = 2019 }