{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T16:21:27Z","timestamp":1783527687551,"version":"3.55.0"},"reference-count":26,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T00:00:00Z","timestamp":1771545600000},"content-version":"vor","delay-in-days":50,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Procedia Computer Science"],"published-print":{"date-parts":[[2026]]},"DOI":"10.1016\/j.procs.2026.02.142","type":"journal-article","created":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T07:17:59Z","timestamp":1774250279000},"page":"1019-1030","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Explainable and Scalable Job Recommendation System using Transformer-based Text Summarization, Cross-Encoder Semantic Similarity, and Ensemble Learning"],"prefix":"10.1016","volume":"277","author":[{"given":"Reham Hesham","family":"El-Deeb","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Walid","family":"Abdelmoez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nashwa","family":"El-Bendary","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.procs.2026.02.142_bib1","doi-asserted-by":"crossref","unstructured":"Panchasara S, Gupta RK, Sharma A. AI Based Job Recommedation System using BERT. In: 2023 7th International Conference On Computing, Communication, Control And Automation (ICCUBEA). Pune, India: IEEE; 2023.","DOI":"10.1109\/ICCUBEA58933.2023.10392119"},{"key":"10.1016\/j.procs.2026.02.142_bib2","doi-asserted-by":"crossref","unstructured":"Sanchan N. Comparative Study on Automated Reference Summary Generation using BERT Models and ROUGE Score Assessment. JCST. 2024; 14(2), 26.","DOI":"10.59796\/jcst.V14N2.2024.26"},{"key":"10.1016\/j.procs.2026.02.142_bib3","doi-asserted-by":"crossref","unstructured":"Liala Almalki. BERT-based Job Recommendation System Using LinkedIn Dataset. JISEM. 2025;10(8s):280\u201391.","DOI":"10.52783\/jisem.v10i8s.1026"},{"key":"10.1016\/j.procs.2026.02.142_bib4","doi-asserted-by":"crossref","unstructured":"Wehnert S, Sudhi V, Dureja S, Kutty L, Shahania S, De Luca EW. Legal norm retrieval with variations of the bert model combined with TF-IDF vectorization. In: Proceedings of the Eighteenth International Conference on Artificial Intelligence and Law. S\u00e3o Paulo Brazil: ACM; 2021. p. 285\u201394.","DOI":"10.1145\/3462757.3466104"},{"key":"10.1016\/j.procs.2026.02.142_bib5","doi-asserted-by":"crossref","unstructured":"Schellingerhout R, Barile F, Tintarev N. A Co-design Study for Multi-Stakeholder Job Recommender System Explanations. arXiv; 2023.","DOI":"10.1007\/978-3-031-44067-0_30"},{"key":"10.1016\/j.procs.2026.02.142_bib6","doi-asserted-by":"crossref","unstructured":"Schellingerhout R. Explainable Multi-Stakeholder Job Recommender Systems. In: 18th ACM Conference on Recommender Systems. Bari Italy: ACM; 2024. p. 1318\u201322.","DOI":"10.1145\/3640457.3688014"},{"key":"10.1016\/j.procs.2026.02.142_bib7","doi-asserted-by":"crossref","unstructured":"Yu X, Qin C, Zhang Q, Zhu C, Ma H, Zhang X, et al. DISCO: A Hierarchical Disentangled Cognitive Diagnosis Framework for Interpretable Job Recommendation. arXiv; 2024.","DOI":"10.1109\/ICDM59182.2024.00066"},{"issue":"1","key":"10.1016\/j.procs.2026.02.142_bib8","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1145\/3645057.3645062","article-title":"Mitigating Algorithm Aversion in Recruiting: A Study on Explainable AI for Conversational Agents","volume":"55","author":"Flei\u00df","year":"2024","journal-title":"SIGMIS Database."},{"key":"10.1016\/j.procs.2026.02.142_bib9","doi-asserted-by":"crossref","unstructured":"Reddy GP, Kumar YVP. Explainable AI (XAI): Explained. In: 2023 IEEE Open Conference of Electrical, Electronic and Information Sciences, Vilnius, Lithuania: IEEE; 2023. p. 1\u20136.","DOI":"10.1109\/eStream59056.2023.10134984"},{"key":"10.1016\/j.procs.2026.02.142_bib10","unstructured":"Ghosh P, Sadaphal V. JobRecoGPT -- Explainable job recommendations using LLMs. arXiv; 2023."},{"key":"10.1016\/j.procs.2026.02.142_bib11","doi-asserted-by":"crossref","unstructured":"Vultureanu-Albi\u015fi A, Murare\u0163u I, B\u0103dic\u0103 C. A Trustworthy and Explainable AI Recommender System: Job Domain Case Study. In: 2024 International Conference on INnovations in Intelligent SysTems and Applications (INISTA). Craiova, Romania: IEEE; 2024. p. 1\u20137.","DOI":"10.1109\/INISTA62901.2024.10683822"},{"issue":"1","key":"10.1016\/j.procs.2026.02.142_bib12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1561\/1500000066","article-title":"Explainable Recommendation: A Survey and New Perspectives","volume":"14","author":"Zhang","year":"2020","journal-title":"FNT in Information Retrieval."},{"issue":"4","key":"10.1016\/j.procs.2026.02.142_bib13","doi-asserted-by":"crossref","first-page":"2207","DOI":"10.1007\/s12525-022-00600-9","article-title":"Applying XAI to an AI-based system for candidate management to mitigate bias and discrimination in hiring","volume":"32","author":"Hofeditz","year":"2022","journal-title":"Electron Markets."},{"key":"10.1016\/j.procs.2026.02.142_bib14","doi-asserted-by":"crossref","unstructured":"Petrov A, Macdonald C. A Systematic Review and Replicability Study of BERT4Rec for Sequential Recommendation. In: Proceedings of the 16th ACM Conference on Recommender Systems. Seattle WA USA: ACM; 2022. p. 436\u201347.","DOI":"10.1145\/3523227.3548487"},{"key":"10.1016\/j.procs.2026.02.142_bib15","doi-asserted-by":"crossref","unstructured":"El-Deeb RH, Abdelmoez W, El-Bendary N. Enhancing E-Recruitment Recommendations Through Text Summarization Techniques. Information. 2025;16(4):333.","DOI":"10.3390\/info16040333"},{"key":"10.1016\/j.procs.2026.02.142_bib16","doi-asserted-by":"crossref","unstructured":"Song K. Efficient Recommendation Systems for Movies Based on BERT4Rec. In: 2023 3rd International Signal Processing, Communications and Engineering Management Conference (ISPCEM). Montreal, QC, Canada: IEEE; 2023. p. 789\u201393.","DOI":"10.1109\/ISPCEM60569.2023.00149"},{"key":"10.1016\/j.procs.2026.02.142_bib17","unstructured":"A. Sachenko, T. Lendiuk, L.-H. Khrystyna, V. Koval, H. Grygoriy, and Y. Halias. Evaluation of ensemble machine learning models for movie recommendation systems. CEUR Workshop Proceedings. 2024."},{"key":"10.1016\/j.procs.2026.02.142_bib18","doi-asserted-by":"crossref","unstructured":"Zhao C, Wu D, Huang J, Yuan Y, Zhang HT, Peng R, et al. BoostTree and BoostForest for Ensemble Learning. IEEE Trans Pattern Anal Mach Intell. 2022;1\u201317.","DOI":"10.1109\/TPAMI.2022.3227370"},{"issue":"3","key":"10.1016\/j.procs.2026.02.142_bib19","doi-asserted-by":"crossref","first-page":"590","DOI":"10.3233\/IDA-240075","article-title":"Explainable paper classification system using topic modeling and SHAP","volume":"29","author":"Shin","year":"2025","journal-title":"Intelligent Data Analysis: An International Journal."},{"key":"10.1016\/j.procs.2026.02.142_bib20","doi-asserted-by":"crossref","unstructured":"Lee AHS, Shankararaman V, Ouh EL. Vision Paper: Advancing of AI Explainability for the Use of ChatGPT in Government Agencies\u2013Proposal of A 4-Step Framework. In: 2023 IEEE International Conference on Big Data (BigData). Sorrento, Italy: IEEE; 2023. p. 5852\u20136.","DOI":"10.1109\/BigData59044.2023.10386797"},{"key":"10.1016\/j.procs.2026.02.142_bib21","doi-asserted-by":"crossref","unstructured":"Longo L, Brcic M, Cabitza F, Choi J, Confalonieri R, Del Ser J, et al. Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions. 2023.","DOI":"10.1016\/j.inffus.2024.102301"},{"issue":"4","key":"10.1016\/j.procs.2026.02.142_bib22","doi-asserted-by":"crossref","first-page":"352","DOI":"10.47852\/bonviewJCCE3202838","article-title":"Comparing BERT Against Traditional Machine Learning Models in Text Classification","volume":"2","author":"Garrido-Merchan","year":"2023","journal-title":"JCCE."},{"key":"10.1016\/j.procs.2026.02.142_bib23","doi-asserted-by":"crossref","unstructured":"Patil A, Suwalka D, Kumar A, Rai G, Saha J. A Survey on Artificial Intelligence (AI) based Job Recommendation Systems. In: 2023 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS). Erode, India: IEEE; 2023. p. 730\u20137.","DOI":"10.1109\/ICSCDS56580.2023.10104718"},{"key":"10.1016\/j.procs.2026.02.142_bib24","doi-asserted-by":"crossref","unstructured":"Alsaif SA, Sassi Hidri M, Ferjani I, Eleraky HA, Hidri A. NLP-Based Bi-Directional Recommendation System: Towards Recommending Jobs to Job Seekers and Resumes to Recruiters. BDCC. 2022;6(4):147.","DOI":"10.3390\/bdcc6040147"},{"issue":"8","key":"10.1016\/j.procs.2026.02.142_bib25","doi-asserted-by":"crossref","first-page":"8363","DOI":"10.1609\/aaai.v38i8.28678","article-title":"Enhancing Job Recommendation through LLM-Based Generative Adversarial Networks","volume":"38","author":"Du","year":"2024","journal-title":"AAAI."},{"key":"10.1016\/j.procs.2026.02.142_bib26","unstructured":"Kaggle Dataset: 1.3M LinkedIn Jobs and Skills dataset, source: https:\/\/www.kaggle.com\/datasets\/asaniczka\/1-3m-linkedin-jobs-and-skills-2024\/, Accessed on: March 2024."}],"container-title":["Procedia Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1877050926002589?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1877050926002589?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T15:43:47Z","timestamp":1783525427000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1877050926002589"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":26,"alternative-id":["S1877050926002589"],"URL":"https:\/\/doi.org\/10.1016\/j.procs.2026.02.142","relation":{},"ISSN":["1877-0509"],"issn-type":[{"value":"1877-0509","type":"print"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Explainable and Scalable Job Recommendation System using Transformer-based Text Summarization, Cross-Encoder Semantic Similarity, and Ensemble Learning","name":"articletitle","label":"Article Title"},{"value":"Procedia Computer Science","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.procs.2026.02.142","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Author(s). Published by Elsevier B.V.","name":"copyright","label":"Copyright"}]}}