{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T04:54:34Z","timestamp":1787028874077,"version":"build-2736575974"},"reference-count":36,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T00:00:00Z","timestamp":1769990400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Leading Talents of Provincial Colleges and Universities, Zhejiang-China","award":["KY20220214000024"],"award-info":[{"award-number":["KY20220214000024"]}]},{"name":"General Program-Education Department of Zhejiang Province","award":["Y202045131"],"award-info":[{"award-number":["Y202045131"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["MAKE"],"abstract":"<jats:p>In an e-learning platform, information retrieval plays an enormous role through efficient processing. Recently, the education sector has increased its trend in online learning systems by generating a large amount of educational content based on student\u2019s criteria. For this sophisticated data analysis scheme, several methods have been employed in recent studies; however, they have suffered from various limitations, including reliability issues, security problems, unauthorized disclosure of data, cost consumption, and interpretability challenges. To tackle these issues, a proposed framework, named the war strategy optimization-based bidirectional long short-term memory (WSO-BiLSTM) model, is designed in this research to reduce sensitivity to local optima and improve convergence stability, thereby achieving robust retrieval performance. With this perspective, the BiLSTM model captures the semantic information of documents in a dual direction for effective retrieval outcomes. Moreover, the model\u2019s key features are extracted effectively by various feature extraction methods. The dynamic movement towards the optimal solution of the WSO algorithm enables the proposed model to retrieve the information more accurately in the information retrieval system. Experiments on an e-learning dataset show that, with a 90% training split, the proposed method achieves 97.90% accuracy, 98.45% precision, 97.90% F1-score, and 97.35% recall.<\/jats:p>","DOI":"10.3390\/make8020033","type":"journal-article","created":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T12:49:44Z","timestamp":1770036584000},"page":"33","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Optimal Information Retrieval System in E-Learning Using Optimization-Driven Bidirectional Long Short-Term Memory"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3637-0447","authenticated-orcid":false,"given":"Hemn Barzan","family":"Abdalla","sequence":"first","affiliation":[{"name":"Department of Computer Science, Wenzhou-Kean University, Wenzhou 325015, China"},{"name":"Department of Computer Science and Technology, Kean University, Union, NJ 07083, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5054-5584","authenticated-orcid":false,"given":"Awder","family":"Ahmed","sequence":"additional","affiliation":[{"name":"Department of Communication Engineering, Technical College of Engineering, Sulaimani Polytechnic University, Sulaymaniyah 46001, Iraq"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,2,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1016\/j.trpro.2023.11.917","article-title":"Using Industry-based Spatio-Temporal Databases to Store and Retrieve Big Traffic Data","volume":"73","author":"Goldner","year":"2023","journal-title":"Transp. Res. Procedia"},{"key":"ref_2","first-page":"100009","article-title":"A fuzzy ontology framework in information retrieval using semantic query expansion","volume":"1","author":"Jain","year":"2021","journal-title":"Int. J. Inf. Manag. Data Insights"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1073","DOI":"10.1016\/j.ijar.2011.05.003","article-title":"Fuzzy ontology representation using OWL 2","volume":"52","author":"Bobillo","year":"2011","journal-title":"Int. J. Approx. Reason."},{"key":"ref_4","unstructured":"Diriye, A., White, R., Buscher, G., and Dumais, S. (November, January 29). Leaving so soon? Understanding and predicting web search abandonment rationales. Proceedings of the 21st ACM International Conference on Information and Knowledge Management, Redmond, WA, USA."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.neucom.2021.04.013","article-title":"QIRM: A quantum interactive retrieval model for session search","volume":"451","author":"Wang","year":"2021","journal-title":"Neurocomputing"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Xing, C., and Wang, K. (2021). Website information retrieval of web database based on symmetric encryption algorithm. J. Ambient. Intell. Humaniz. Comput., 1\u201312.","DOI":"10.1007\/s12652-020-02819-w"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.optlaseng.2019.01.015","article-title":"Securing multiple information using wavelet transform and Yang-Gu mixture amplitude-phase retrieval algorithm","volume":"118","author":"Abuturab","year":"2019","journal-title":"Opt. Lasers Eng."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"9891","DOI":"10.1007\/s12652-020-02736-y","article-title":"PAPIR: Privacy-aware personalized information retrieval","volume":"12","author":"Saadi","year":"2021","journal-title":"J. Ambient. Intell. Humaniz. Comput."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2447","DOI":"10.1109\/TASLP.2018.2852739","article-title":"Interactive spoken content retrieval by deep reinforcement learning","volume":"26","author":"Lee","year":"2018","journal-title":"IEEE\/ACM Trans. Audio Speech Lang. Process."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.future.2019.04.022","article-title":"DStore: A distributed system for outsourced data storage and retrieval","volume":"99","author":"Xue","year":"2019","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"6643","DOI":"10.1007\/s10115-024-02152-0","article-title":"Optimal intelligent information retrieval and reliable storage scheme for cloud environment and E-learning big data analytics","volume":"66","author":"Venkatachalam","year":"2024","journal-title":"Knowl. Inf. Syst."},{"key":"ref_12","unstructured":"Izacard, G., Caron, M., Hosseini, L., Riedel, S., Bojanowski, P., Joulin, A., and Grave, E. (2021). Unsupervised dense information retrieval with contrastive learning. arXiv."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Zhu, R., Tu, X., and Huang, J.X. (2020). Deep learning on information retrieval and its applications. Deep Learning for Data Analytics, Academic Press.","DOI":"10.1016\/B978-0-12-819764-6.00008-9"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"26889","DOI":"10.1007\/s11042-021-10998-7","article-title":"Secure content-based image retrieval system using deep learning with a multi-share creation scheme in a cloud environment","volume":"80","author":"Punithavathi","year":"2021","journal-title":"Multimed. Tools Appl."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1007\/s11277-021-08211-x","article-title":"Ensembling of text and images using deep convolutional neural networks for intelligent information retrieval","volume":"127","author":"Mahalakshmi","year":"2022","journal-title":"Wirel. Pers. Commun."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Lu, R.S., Lin, C.C., and Tsao, H.Y. (2024). Empowering Large Language Models to Leverage Domain-Specific Knowledge in E-Learning. Appl. Sci., 14.","DOI":"10.3390\/app14125264"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Shi, T., Li, L., Lin, Z., Yang, T., Quan, X., and Wang, Q. (2023). Dual-feedback knowledge retrieval for task-oriented dialogue systems. arXiv.","DOI":"10.18653\/v1\/2023.emnlp-main.405"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Tahir, A., Chen, F., Hayat, B., Shaheen, Q., Ming, Z., Ahmad, A., Kim, K.I., and Lim, B.H. (2023). Hybrid hp-boa: An optimized framework for reliable storage of cloud data using a hybrid meta-heuristic algorithm. Appl. Sci., 13.","DOI":"10.3390\/app13095346"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2447","DOI":"10.17485\/IJST\/v16i31.833","article-title":"A SEMWORD-based Semantic Secure Content Retrieval System in E-learning","volume":"16","author":"Eunaicy","year":"2023","journal-title":"Indian J. Sci. Technol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1007\/s10791-021-09398-0","article-title":"Neural ranking models for document retrieval","volume":"24","author":"Trabelsi","year":"2021","journal-title":"Inf. Retr. J."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"14907","DOI":"10.1007\/s10462-023-10508-1","article-title":"Intelligent techniques in e-learning: A literature review","volume":"56","author":"Kopanja","year":"2023","journal-title":"Artif. Intell. Rev."},{"key":"ref_22","unstructured":"(2025, July 15). CISI Dataset. Available online: https:\/\/www.kaggle.com\/datasets\/dmaso01dsta\/cisi-a-dataset-for-information-retrieval."},{"key":"ref_23","unstructured":"(2025, July 15). E-Learning Dataset. Available online: https:\/\/www.kaggle.com\/datasets\/marlonferrari\/elearning-student-reactions."},{"key":"ref_24","unstructured":"(2025, July 15). Course Recommendation System Dataset. Available online: https:\/\/www.kaggle.com\/datasets\/shailx\/course-recommendation-system-dataset."},{"key":"ref_25","first-page":"534","article-title":"NoSQL: A collection of documents and cloud by using a dynamic web query form","volume":"Volume 9631","author":"Abdalla","year":"2015","journal-title":"Proceedings of the Seventh International Conference on Digital Image Processing (ICDIP 2015)"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Bonde, S.Y., and Bhadade, U.S. (2017, January 17\u201318). Analysis of encryption algorithms (RSA, SRNN, and 2 key pair) for information security. Proceedings of the 2017 International Conference on Computing, Communication, Control and Automation (ICCUBEA), Pune, India.","DOI":"10.1109\/ICCUBEA.2017.8463720"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"142","DOI":"10.3991\/ijet.v11i04.5654","article-title":"WordNet and cosine similarity-based classifier of exam questions using Bloom\u2019s taxonomy","volume":"11","author":"Jayakodi","year":"2016","journal-title":"Int. J. Emerg. Technol. Learn."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"285","DOI":"10.21512\/comtech.v7i4.3746","article-title":"Single document automatic text summarization using the term frequency-inverse document frequency (TF-IDF)","volume":"7","author":"Christian","year":"2016","journal-title":"ComTech: Comput. Math. Eng. Appl."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"52177","DOI":"10.1109\/ACCESS.2021.3069001","article-title":"An enhanced hybrid feature selection technique using term frequency-inverse document frequency and support vector machine-recursive feature elimination for sentiment classification","volume":"9","author":"Nafis","year":"2021","journal-title":"IEEE Access"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Qader, W.A., Ameen, M.M., and Ahmed, B.I. (2019, January 23\u201325). An overview of bag of words; importance, implementation, applications, and challenges. Proceedings of the 2019 International Engineering Conference (IEC), Erbil, Iraq.","DOI":"10.1109\/IEC47844.2019.8950616"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"4947","DOI":"10.1007\/s10660-024-09888-5","article-title":"Hybrid self-attention BiLSTM and incentive learning-based collaborative filtering for e-commerce recommendation systems","volume":"25","author":"Abdalla","year":"2024","journal-title":"Electron. Commer. Res."},{"key":"ref_32","first-page":"513","article-title":"An Efficient Recommendation System in E-commerce Using Passer Learning Optimization Based on Bi-LSTM","volume":"4","author":"Abdalla","year":"2025","journal-title":"J. Comput. Cogn. Eng."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Mahalakshmi, P., and Fatima, N.S. (2020, January 3\u20135). Collaborative text and image-based information retrieval model using Bilstm and residual networks. Proceedings of the 2020 3rd International Conference on Intelligent Sustainable Systems (ICISS), Thoothukudi, India.","DOI":"10.1109\/ICISS49785.2020.9315886"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"13","DOI":"10.31449\/inf.v48i13.6063","article-title":"Retrieval and Analysis of Multimedia Data of Robot Deep Neural Network Based on Deep Learning and Information Fusion","volume":"48","author":"Guo","year":"2024","journal-title":"Informatica"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"25073","DOI":"10.1109\/ACCESS.2022.3153493","article-title":"War strategy optimization algorithm: A new effective metaheuristic algorithm for global optimization","volume":"10","author":"Ayyarao","year":"2022","journal-title":"IEEE Access"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Felder\u2013Silverman Learning Style Model (FSLSM), Hussain, T., Yu, L., Asim, M., Ahmed, A., and Wani, M.A. (2024). Enhancing e-learning adaptability with automated learning style identification and sentiment analysis: A hybrid deep learning approach for smart education. Information, 15.","DOI":"10.3390\/info15050277"}],"container-title":["Machine Learning and Knowledge Extraction"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2504-4990\/8\/2\/33\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T13:21:09Z","timestamp":1770038469000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2504-4990\/8\/2\/33"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2,2]]},"references-count":36,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2026,2]]}},"alternative-id":["make8020033"],"URL":"https:\/\/doi.org\/10.3390\/make8020033","relation":{},"ISSN":["2504-4990"],"issn-type":[{"value":"2504-4990","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2,2]]}}}