E-textbook enrichment using graph based e-content recommendation
| dc.contributor.author | Kushwaha R.C.; Singhal A.; Biswas A. | |
| dc.date.accessioned | 2025-05-23T11:30:16Z | |
| dc.description.abstract | This 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.doi | https://doi.org/10.1166/jctn.2020.8696 | |
| dc.identifier.uri | http://172.23.0.11:4000/handle/123456789/11980 | |
| dc.relation.ispartofseries | Journal of Computational and Theoretical Nanoscience | |
| dc.title | E-textbook enrichment using graph based e-content recommendation |