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E-textbook enrichment using graph based e-content recommendation

dc.contributor.authorKushwaha R.C.; Singhal A.; Biswas A.
dc.date.accessioned2025-05-23T11:30:16Z
dc.description.abstractThis paper presents a novel computational technique for the enrichment of E-textbook using the recommendation of the open courseware, YouTube Videos, Wikipedia articles, Slideshare, Geogebra Applets and other relevant web contents. The research work is based on NCERT secondary class mathematics E-Textbook to improve the learning deficiency by enrichment of the book using augmentation of the relevant web contents. The text mining tool is used for the enrichment of the E-textbook using the relevant E-resources available from the web. A phrase graph based algorithmic framework has been developed to extract the mathematical concepts from the E-textbook and recommend the E-contents to the enrichment of the E-textbook. The proposed method provides more precise and relevant recommendations in comparison to the available methods. © 2020 American Scientific Publishers.
dc.identifier.doihttps://doi.org/10.1166/jctn.2020.8696
dc.identifier.urihttp://172.23.0.11:4000/handle/123456789/11980
dc.relation.ispartofseriesJournal of Computational and Theoretical Nanoscience
dc.titleE-textbook enrichment using graph based e-content recommendation

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