{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,12]],"date-time":"2025-07-12T00:40:01Z","timestamp":1752280801582,"version":"3.41.2"},"reference-count":21,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2025,7,11]],"date-time":"2025-07-11T00:00:00Z","timestamp":1752192000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,7,11]],"date-time":"2025-07-11T00:00:00Z","timestamp":1752192000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["SN COMPUT. SCI."],"DOI":"10.1007\/s42979-025-04186-9","type":"journal-article","created":{"date-parts":[[2025,7,11]],"date-time":"2025-07-11T11:43:15Z","timestamp":1752234195000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Augmenting Course Recommendations with Explainable AI: A Hybrid Approach Utilizing Large Language Models"],"prefix":"10.1007","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-7842-5917","authenticated-orcid":false,"given":"Ahan","family":"Ganguly","sequence":"first","affiliation":[]},{"given":"Ankan","family":"Dey","sequence":"additional","affiliation":[]},{"given":"Sourik","family":"Bhuiya","sequence":"additional","affiliation":[]},{"given":"Indranil Roy","family":"Banik","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1643-1337","authenticated-orcid":false,"given":"Subhabrata","family":"Sengupta","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3713-2459","authenticated-orcid":false,"given":"Rupayan","family":"Das","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,7,11]]},"reference":[{"key":"4186_CR1","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1007\/978-0-387-85820-3_3","volume-title":"Recommender systems handbook","author":"P Lops","year":"2011","unstructured":"Lops P, de Gemmis M, Semeraro G. Content-based recommender systems: state of the Art and trends. In: Ricci F, Rokach L, Shapira B, editors. Recommender systems handbook. Boston, MA: Springer; 2011. pp. 73\u2013105. https:\/\/doi.org\/10.1007\/978-0-387-85820-3_3."},{"key":"4186_CR2","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1109\/ISRITI54043.2021.9702789","volume-title":"2021 4th international seminar on research of information technology and intelligent systems (ISRITI)","author":"Y Adilaksa","year":"2021","unstructured":"Adilaksa Y, Musdholifah A. Recommendation system for elective courses using content-based filtering and weighted cosine similarity. 2021 4th international seminar on research of information technology and intelligent systems (ISRITI). Indonesia: Yogyakarta; 2021. pp. 51\u20135. https:\/\/doi.org\/10.1109\/ISRITI54043.2021.9702789."},{"key":"4186_CR3","doi-asserted-by":"publisher","unstructured":"Adomavicius G, Tuzhilin A. Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions, IEEE Transactions on Knowledge and Data Engineering, vol. 17, no. 6, pp. 734\u2013749, Jun. 2005, https:\/\/doi.org\/10.1109\/TKDE.2005.99","DOI":"10.1109\/TKDE.2005.99"},{"key":"4186_CR4","doi-asserted-by":"publisher","unstructured":"Lee EL, Kuo T-T, Lin S-D. A collaborative filtering-based two stage model with item dependency for course recommendation, in Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM \u201818), Torino, Italy, 2018, pp. 1647\u20131650. https:\/\/doi.org\/10.1145\/3269206.3269317","DOI":"10.1145\/3269206.3269317"},{"key":"4186_CR5","unstructured":"Zhalgassova Z, Shaikym A, Sadyk U, Assangali B. A collaborative filtering based approach for recommending elective courses, in Proceedings of the 2020 International Conference on Information and Communication Technologies in Education (ICTE \u201820), Almaty, Kazakhstan, 2020, pp. 123\u2013130."},{"key":"4186_CR6","doi-asserted-by":"publisher","unstructured":"Chang P-C, Lin C, Chen M. A hybrid course recommendation system by integrating collaborative filtering and artificial immune systems, Algorithms, vol. 9, no. 3, p. 47, 2016, https:\/\/doi.org\/10.3390\/a9030047","DOI":"10.3390\/a9030047"},{"key":"4186_CR7","doi-asserted-by":"publisher","unstructured":"George T, Merugu S. A scalable collaborative filtering framework based on co-clustering, in Fifth IEEE International Conference on Data Mining (ICDM\u201905), Houston, TX, USA, 2005, pp. 625\u2013628. https:\/\/doi.org\/10.1109\/ICDM.2005.14","DOI":"10.1109\/ICDM.2005.14"},{"key":"4186_CR8","doi-asserted-by":"publisher","unstructured":"Jovanovi\u0107 M, Ga\u0161evi\u0107 D, Deved\u017ei\u0107 V. Ontology-based recommender system for e-learning platform, in Proceedings of the 6th International Conference on Web Information Systems Engineering (WISE\u201905), New York, NY, USA, 2005, pp. 66\u201377. https:\/\/doi.org\/10.1007\/11581062_6","DOI":"10.1007\/11581062_6"},{"issue":"2","key":"4186_CR9","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1177\/0047239519868817","volume":"48","author":"AA Adewole","year":"2019","unstructured":"Adewole AA, Adeyemo OS. A knowledge-based hybrid recommender system for educational data mining. J Educational Technol Syst. 2019;48(2):234\u201356. https:\/\/doi.org\/10.1177\/0047239519868817.","journal-title":"J Educational Technol Syst"},{"key":"4186_CR10","doi-asserted-by":"publisher","unstructured":"Wang H, Zhang F, Zhao M, Li W, Xie X, Guo M. Multi-task feature learning for knowledge graph enhanced recommendation, in Proceedings of the 2019 World Wide Web Conference (WWW \u201819), San Francisco, CA, USA, 2019, pp. 2000\u20132010. https:\/\/doi.org\/10.1145\/3308558.3313411","DOI":"10.1145\/3308558.3313411"},{"key":"4186_CR11","doi-asserted-by":"publisher","unstructured":"Pardos ZA, Jiang W. Combating the filter bubble: Designing for serendipity in a university course recommendation system, in Proceedings of the 10th International Conference on Learning Analytics & Knowledge (LAK \u201820), Frankfurt, Germany, 2020, pp. 350\u2013359. https:\/\/doi.org\/10.1145\/3375462.3375525","DOI":"10.1145\/3375462.3375525"},{"key":"4186_CR12","unstructured":"Pardos ZA, Jiang W. An LLM approach to course recommendations using natural language queries, in Proceedings of the 14th International Conference on Educational Data Mining (EDM \u201821), Paris, France, 2021, pp. 412\u2013417."},{"key":"4186_CR13","doi-asserted-by":"publisher","unstructured":"Wu L et al. A survey on large language models for recommendation, arXiv preprint arXiv:2305.19860, 2023. https:\/\/doi.org\/10.48550\/arXiv.2305.19860","DOI":"10.48550\/arXiv.2305.19860"},{"key":"4186_CR14","doi-asserted-by":"publisher","unstructured":"Devlin J, Chang M-W, Lee K, Toutanova K. BERT: Pre-training of deep bidirectional transformers for language understanding, in Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT \u201819), Minneapolis, MN, USA, 2019, pp. 4171\u20134186. https:\/\/doi.org\/10.18653\/v1\/N19-1423","DOI":"10.18653\/v1\/N19-1423"},{"key":"4186_CR15","doi-asserted-by":"publisher","unstructured":"Van Deventer H, Mills M, Evrard AE. From Interests to Insights: An LLM Approach to Course Recommendations Using Natural Language Queries, arXiv preprint arXiv:2412.19312, Dec. 2024. https:\/\/doi.org\/10.48550\/arXiv.2412.19312","DOI":"10.48550\/arXiv.2412.19312"},{"key":"4186_CR16","doi-asserted-by":"publisher","unstructured":"Luo Y, Cheng M, Zhang H, Lu J, Liu Q, Chen E. Unlocking the Potential of Large Language Models for Explainable Recommendations, arXiv preprint arXiv:2312.15661, Dec. 2023. https:\/\/doi.org\/10.48550\/arXiv.2312.15661","DOI":"10.48550\/arXiv.2312.15661"},{"issue":"3","key":"4186_CR17","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1080\/10864415.2016.1174055","volume":"20","author":"D Jannach","year":"2016","unstructured":"Jannach D, Zanker M. Knowledge-based recommender systems: overview and research opportunities. Int J Electron Commer. 2016;20(3):3\u201331. https:\/\/doi.org\/10.1080\/10864415.2016.1174055.","journal-title":"Int J Electron Commer"},{"key":"4186_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-1-4899-7637-6_1","volume-title":"Recommender systems handbook","author":"F Ricci","year":"2015","unstructured":"Ricci F, Rokach L, Shapira B. Introduction to recommender systems handbook. In: Ricci F, Rokach L, Shapira B, editors. Recommender systems handbook. 2nd ed. Boston, MA: Springer; 2015. pp. 1\u201335. https:\/\/doi.org\/10.1007\/978-1-4899-7637-6_1.","edition":"2"},{"key":"4186_CR19","doi-asserted-by":"publisher","unstructured":"Sengupta S, Das R, Chakrabarti S. A Deep Dive into a Groundbreaking Approach to Machine Learning-Powered E-Learning. EMITER EMITTER International Journal of Engineering Technology. Vol 12 No 2 (2024). https:\/\/doi.org\/10.24003\/emitter.v12i2.855","DOI":"10.24003\/emitter.v12i2.855"},{"key":"4186_CR20","doi-asserted-by":"publisher","unstructured":"Sengupta, S., Das, R. & Chakrabarti, S. Hybrid Data Mining Techniques for Predicting Student Academic Performance in E-Learning to Avoid Drop-Out (HDL-SP): An Efficient Data Mining Technique to Forecast Academic Performances of Students. SN COMPUT. SCI. 6, 162 (2025). https:\/\/doi.org\/10.1007\/s42979-025-03733-8","DOI":"10.1007\/s42979-025-03733-8"},{"key":"4186_CR21","doi-asserted-by":"publisher","unstructured":"Sengupta, S., Das, R., Bardhan, S. et al. Smart E-Learning, Smarter SEO: The Winning Formula. SN COMPUT. SCI. 6, 606 (2025). https:\/\/doi.org\/10.1007\/s42979-025-04136-5","DOI":"10.1007\/s42979-025-04136-5"}],"container-title":["SN Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42979-025-04186-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s42979-025-04186-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42979-025-04186-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,12]],"date-time":"2025-07-12T00:03:04Z","timestamp":1752278584000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s42979-025-04186-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,11]]},"references-count":21,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2025,8]]}},"alternative-id":["4186"],"URL":"https:\/\/doi.org\/10.1007\/s42979-025-04186-9","relation":{},"ISSN":["2661-8907"],"issn-type":[{"type":"electronic","value":"2661-8907"}],"subject":[],"published":{"date-parts":[[2025,7,11]]},"assertion":[{"value":"3 March 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 July 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 July 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors certify that they have NO affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers\u2019 bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interests (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"Approval was obtained from the local ethics committee.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}}],"article-number":"634"}}