{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T20:12:47Z","timestamp":1776111167210,"version":"3.50.1"},"reference-count":165,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,6,2]],"date-time":"2025-06-02T00:00:00Z","timestamp":1748822400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,6,2]],"date-time":"2025-06-02T00:00:00Z","timestamp":1748822400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Big Data"],"DOI":"10.1186\/s40537-025-01173-y","type":"journal-article","created":{"date-parts":[[2025,6,2]],"date-time":"2025-06-02T06:55:56Z","timestamp":1748847356000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Job recommender systems: a systematic literature review, applications, open issues, and challenges"],"prefix":"10.1186","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1380-705X","authenticated-orcid":false,"given":"Duygu","family":"\u00c7elik Ertu\u011frul","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3575-5855","authenticated-orcid":false,"given":"Selin","family":"Bitirim","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,6,2]]},"reference":[{"key":"1173_CR1","volume-title":"Context-aware recommender systems","author":"G Adomavicius","year":"2011","unstructured":"Adomavicius G, Tuzhilin A. Context-aware recommender systems. Boston, MA: Springer; 2011."},{"key":"1173_CR2","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1016\/j.glt.2021.11.001","volume":"3","author":"A Al-Habaibeh","year":"2021","unstructured":"Al-Habaibeh A, Watkins M, Waried K, Javareshk MB. Challenges and opportunities of remotely working from home during Covid-19 pandemic. Global Transitions. 2021;3:99\u2013108.","journal-title":"Global Transitions"},{"key":"1173_CR3","doi-asserted-by":"publisher","DOI":"10.1109\/IISA.2014.6878720","volume-title":"A content-based approach for recommending personnel for job positions","author":"ND Almalis","year":"2014","unstructured":"Almalis ND, Tsihrintzis GA, Karagiannis N. A content-based approach for recommending personnel for job positions. New York: IEEE; 2014."},{"key":"1173_CR4","doi-asserted-by":"publisher","DOI":"10.1109\/IISA.2015.7388018","volume-title":"FoDRA\u2014A new content-based job recommendation algorithm for job seeking and recruiting","author":"ND Almalis","year":"2015","unstructured":"Almalis ND, Tsihrintzis GA, Karagiannis N, Strati AD. FoDRA\u2014A new content-based job recommendation algorithm for job seeking and recruiting. New York: IEEE; 2015."},{"issue":"3","key":"1173_CR5","doi-asserted-by":"publisher","first-page":"511","DOI":"10.1007\/s11704-016-5241-z","volume":"11","author":"S Al-Otaibi","year":"2017","unstructured":"Al-Otaibi S, Ykhlef M. Hybrid immunizing solution for job recommender system. Front Comp Sci. 2017;11(3):511\u201327.","journal-title":"Front Comp Sci"},{"key":"1173_CR6","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1016\/j.knosys.2016.03.006","volume":"100","author":"MYH Al-Shamri","year":"2016","unstructured":"Al-Shamri MYH. User profiling approaches for demographic recommender systems. Knowl-Based Syst. 2016;100:175\u201387.","journal-title":"Knowl-Based Syst"},{"key":"1173_CR7","doi-asserted-by":"publisher","DOI":"10.1109\/CCWC51732.2021.9376008","volume-title":"Addressing data sparsity in collaborative filtering-based recommender systems using clustering and artificial neural network","author":"A Althbiti","year":"2021","unstructured":"Althbiti A, Alshamrani R, Alghamdi T, Lee S, Ma X. Addressing data sparsity in collaborative filtering-based recommender systems using clustering and artificial neural network. New York: IEEE; 2021."},{"key":"1173_CR8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-66218-9_8","volume-title":"A study on intervention of chatbots in recruitment","author":"K Anitha","year":"2021","unstructured":"Anitha K, Shanthi V. A study on intervention of chatbots in recruitment. Cham: Springer; 2021."},{"issue":"1","key":"1173_CR9","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/s10479-016-2154-z","volume":"256","author":"I Aouadni","year":"2017","unstructured":"Aouadni I, Rebai A. Decision support system based on genetic algorithm and multi-criteria satisfaction analysis (MUSA) method for measuring job satisfaction. Ann Oper Res. 2017;256(1):3\u201320.","journal-title":"Ann Oper Res"},{"issue":"3","key":"1173_CR10","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1097\/01.NAJ.0000444496.24228.2c","volume":"114","author":"E Aromataris","year":"2014","unstructured":"Aromataris E, Pearson A. The systematic review: an overview. AJN Am J Nurs. 2014;114(3):53\u20138.","journal-title":"AJN Am J Nurs"},{"key":"1173_CR11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-45135-5_10","volume-title":"Dimensions and metrics for evaluating recommendation systems","author":"I Avazpour","year":"2014","unstructured":"Avazpour I, Pitakrat T, Grunske L, Grundy J. Dimensions and metrics for evaluating recommendation systems. Berlin, Heidelberg: Springer; 2014."},{"key":"1173_CR12","doi-asserted-by":"publisher","DOI":"10.1109\/ICOIN.2018.8343073","volume-title":"A Jaccard base similarity measure to improve performance of CF based recommender systems","author":"M Ayub","year":"2018","unstructured":"Ayub M, Ghazanfar MA, Maqsood M, Saleem A. A Jaccard base similarity measure to improve performance of CF based recommender systems. New York: IEEE; 2018."},{"issue":"6","key":"1173_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.heliyon.2021.e07233","volume":"7","author":"MR Azizi","year":"2021","unstructured":"Azizi MR, Atlasi R, Ziapour A, Abbas J, Naemi R. Innovative human resource management strategies during the COVID-19 pandemic: a systematic narrative review approach. Heliyon. 2021;7(6): e07233.","journal-title":"Heliyon"},{"key":"1173_CR14","doi-asserted-by":"publisher","DOI":"10.1109\/SIET48054.2019.8985988","volume-title":"Employee recruitment recommendation using profile matching and Na\u00efve Bayes","author":"FA Bachtiar","year":"2019","unstructured":"Bachtiar FA, Pradana F, Yudiari RD. Employee recruitment recommendation using profile matching and Na\u00efve Bayes. New York: IEEE; 2019."},{"issue":"4","key":"1173_CR15","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1007\/s00799-015-0156-0","volume":"17","author":"J Beel","year":"2016","unstructured":"Beel J, Gipp B, Langer S, Breitinger C. Paper recommender systems: a literature survey. Int J Digit Libr. 2016;17(4):305\u201338.","journal-title":"Int J Digit Libr"},{"key":"1173_CR16","volume-title":"Predicting the users' clickstreams using time series representation, symbolic sequences, and deep learning: application on job offers recommendation tasks","author":"S Benabderrahmane","year":"2017","unstructured":"Benabderrahmane S, Mellouli N, Lamolle M. Predicting the users\u2019 clickstreams using time series representation, symbolic sequences, and deep learning: application on job offers recommendation tasks. New York: IEEE; 2017."},{"key":"1173_CR17","doi-asserted-by":"publisher","first-page":"857","DOI":"10.1016\/j.procs.2019.12.060","volume":"162","author":"J Bernab\u00e9-Moreno","year":"2019","unstructured":"Bernab\u00e9-Moreno J, Tejeda-Lorente \u00c1, Herce-Zelaya J, Porcel C, Herrera-Viedma E. An automatic skills standardization method based on subject expert knowledge extraction and semantic matching. Procedia Comput Sci. 2019;162:857\u201364.","journal-title":"Procedia Comput Sci"},{"key":"1173_CR18","doi-asserted-by":"publisher","DOI":"10.1109\/ICOEI53556.2022.9777116","volume-title":"Comparative performance evaluation of web-based book recommender systems","author":"SS Bhat","year":"2022","unstructured":"Bhat SS, Pranav P, Shashank KV, Raghunandan A, Mohan BR. Comparative performance evaluation of web-based book recommender systems. New York: IEEE; 2022."},{"key":"1173_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107134","volume":"226","author":"M Birjali","year":"2021","unstructured":"Birjali M, Kasri M, Beni-Hssane A. A comprehensive survey on sentiment analysis: approaches, challenges and trends. Knowl-Based Syst. 2021;226: 107134.","journal-title":"Knowl-Based Syst"},{"key":"1173_CR20","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1016\/j.knosys.2013.03.012","volume":"46","author":"J Bobadilla","year":"2013","unstructured":"Bobadilla J, Ortega F, Hernando A, Guti\u00e9rrez A. Recommender systems survey. Knowledge-Based Syst. 2013;46:109\u201332.","journal-title":"Knowledge-Based Syst"},{"issue":"1","key":"1173_CR21","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1108\/IJM-03-2014-0083","volume":"37","author":"G Boccuzzo","year":"2016","unstructured":"Boccuzzo G, Fabbris L, Paccagnella O. Job-major match and job satisfaction in Italy. Int J Manpow. 2016;37(1):135\u201356.","journal-title":"Int J Manpow"},{"key":"1173_CR22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-11647-6_90","volume-title":"Investigating natural language processing techniques for a recommendation system to support employers, job seekers and educational institutions","author":"K Bothmer","year":"2022","unstructured":"Bothmer K, Schlippe T. Investigating natural language processing techniques for a recommendation system to support employers, job seekers and educational institutions. Cham: Springer International Publishing; 2022."},{"issue":"3","key":"1173_CR23","first-page":"13","volume":"32","author":"R Burke","year":"2011","unstructured":"Burke R, Felfernig A, G\u00f6ker MH. Recommender systems: an overview. AI Mag. 2011;32(3):13\u20138.","journal-title":"AI Mag"},{"issue":"6","key":"1173_CR24","doi-asserted-by":"publisher","first-page":"1487","DOI":"10.3233\/IDA-163209","volume":"21","author":"E \u00c7ano","year":"2017","unstructured":"\u00c7ano E, Morisio M. Hybrid recommender systems: a systematic literature review. Intell Data Anal. 2017;21(6):1487\u2013524.","journal-title":"Intell Data Anal"},{"issue":"1","key":"1173_CR25","doi-asserted-by":"publisher","first-page":"141","DOI":"10.3906\/elk-1304-130","volume":"24","author":"D \u00c7elik","year":"2016","unstructured":"\u00c7elik D. Towards a semantic-based information extraction system for matching r\u00e9sum\u00e9s to job openings. Turk J Electr Eng Comput Sci. 2016;24(1):141\u201359.","journal-title":"Turk J Electr Eng Comput Sci"},{"key":"1173_CR26","volume-title":"A semantic search agent approach: finding appropriate semantic Web services based on user request term (s)","author":"D Celik","year":"2005","unstructured":"Celik D, Elci A. A semantic search agent approach: finding appropriate semantic Web services based on user request term (s). New York: IEEE; 2005."},{"key":"1173_CR27","doi-asserted-by":"publisher","DOI":"10.1109\/COMPSAC.2006.127","volume-title":"Discovery and scoring of semantic web services based on client requirement (s) through a semantic search agent","author":"D Celik","year":"2006","unstructured":"Celik D, Elci A. Discovery and scoring of semantic web services based on client requirement (s) through a semantic search agent. New York: IEEE; 2006."},{"issue":"3","key":"1173_CR28","doi-asserted-by":"publisher","first-page":"315","DOI":"10.3233\/MGS-2008-4306","volume":"4","author":"D Celik","year":"2008","unstructured":"Celik D, Elci A. Provision of semantic Web services through an intelligent semantic Web service finder. Multiagent Grid Syst. 2008;4(3):315\u201334.","journal-title":"Multiagent Grid Syst"},{"key":"1173_CR29","first-page":"157","volume":"133","author":"D \u00c7elik","year":"2011","unstructured":"\u00c7elik D, El\u00e7i A. Ontology-based matchmaking and composition of business processes. Sem Agent Syst: Found Applic. 2011;133:157.","journal-title":"Sem Agent Syst: Found Applic"},{"key":"1173_CR30","volume-title":"Towards an information extraction system based on ontology to match resumes and jobs","author":"D \u00c7elik","year":"2013","unstructured":"\u00c7elik D, Karakas A, Bal G, G\u00fcltunca C, El\u00e7i A, Buluz B, Alevli MC. Towards an information extraction system based on ontology to match resumes and jobs. New York: IEEE; 2013."},{"issue":"4","key":"1173_CR31","doi-asserted-by":"publisher","DOI":"10.1111\/exsy.12519","volume":"37","author":"D \u00c7elik Ertu\u011frul","year":"2020","unstructured":"\u00c7elik Ertu\u011frul D, El\u00e7i A. A survey on semanticized and personalized health recommender systems. Expert Syst. 2020;37(4): e12519.","journal-title":"Expert Syst"},{"key":"1173_CR32","doi-asserted-by":"publisher","DOI":"10.1109\/ICMLA.2017.00-96","volume-title":"Evaluating non-personalized single-heuristic active learning strategies for collaborative filtering recommender systems","author":"G Chaaya","year":"2017","unstructured":"Chaaya G, M\u00e9tais E, Abdo JB, Chiky R, Demerjian J, Barbar K. Evaluating non-personalized single-heuristic active learning strategies for collaborative filtering recommender systems. New York: IEEE; 2017."},{"key":"1173_CR33","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-45817-5_44","volume-title":"A hadoop-based database querying approach for non-expert Users","author":"Y Chai","year":"2016","unstructured":"Chai Y, Wang C, Wen Y, Yuan X. A hadoop-based database querying approach for non-expert Users. Cham: Springer; 2016."},{"key":"1173_CR34","doi-asserted-by":"publisher","DOI":"10.1109\/ICCEM47450.2020.9219491","volume-title":"Based on the application of AI technology in resume analysis and job recommendation","author":"YC Chou","year":"2020","unstructured":"Chou YC, Yu HY. Based on the application of AI technology in resume analysis and job recommendation. New York: IEEE; 2020."},{"issue":"12","key":"1173_CR35","first-page":"1437","volume":"9","author":"S Colucci","year":"2003","unstructured":"Colucci S, Di Noia T, Di Sciascio E, Donini FM, Mongiello M, Mottola M. A formal approach to ontology-based semantic match of skills descriptions. J Univers Comput Sci. 2003;9(12):1437\u201354.","journal-title":"J Univers Comput Sci"},{"key":"1173_CR36","doi-asserted-by":"publisher","DOI":"10.5120\/ijca2017913081","author":"D Das","year":"2017","unstructured":"Das D, Sahoo L, Datta S. A survey on recommendation system. Int J Comput Appli. 2017. https:\/\/doi.org\/10.5120\/ijca2017913081.","journal-title":"Int J Comput Appli"},{"key":"1173_CR37","volume-title":"Job recommender systems: a survey","author":"J Dhameliya","year":"2019","unstructured":"Dhameliya J, Desai N. Job recommender systems: a survey. New York: IEEE; 2019."},{"key":"1173_CR38","doi-asserted-by":"publisher","DOI":"10.1109\/RCIS.2014.6861048","volume-title":"Taxonomy-based job recommender systems on Facebook and LinkedIn profiles","author":"M Diaby","year":"2014","unstructured":"Diaby M, Viennet E. Taxonomy-based job recommender systems on Facebook and LinkedIn profiles. New York: IEEE; 2014."},{"key":"1173_CR39","volume-title":"Job and candidate recommendation with big data support: a contextual online learning approach","author":"S Dong","year":"2017","unstructured":"Dong S, Lei Z, Zhou P, Bian K, Liu G. Job and candidate recommendation with big data support: a contextual online learning approach. New York: IEEE; 2017."},{"issue":"10","key":"1173_CR40","doi-asserted-by":"publisher","first-page":"866","DOI":"10.1016\/j.datak.2011.06.004","volume":"70","author":"C Dorn","year":"2011","unstructured":"Dorn C, Skopik F, Schall D, Dustdar S. Interaction mining and skill-dependent recommendations for multi-objective team composition. Data Knowl Eng. 2011;70(10):866\u201391.","journal-title":"Data Knowl Eng"},{"issue":"8","key":"1173_CR41","first-page":"8363","volume":"38","author":"Y Du","year":"2024","unstructured":"Du Y, Luo D, Yan R, Wang X, Liu H, Zhu H, Zhang J. Enhancing job recommendation through llm-based generative adversarial networks. Proc AAAI Conf Artif Intell. 2024;38(8):8363\u201371.","journal-title":"Proc AAAI Conf Artif Intell"},{"issue":"9","key":"1173_CR42","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3561048","volume":"55","author":"R Dwivedi","year":"2023","unstructured":"Dwivedi R, Dave D, Naik H, Singhal S, Omer R, Patel P, Ranjan R. Explainable AI (XAI): Core ideas, techniques, and solutions. ACM Comput Surv. 2023;55(9):1\u201333.","journal-title":"ACM Comput Surv"},{"key":"1173_CR43","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.118823","volume":"213","author":"M Etemadi","year":"2023","unstructured":"Etemadi M, Abkenar SB, Ahmadzadeh A, Kashani MH, Asghari P, Akbari M, Mahdipour E. A systematic review of healthcare recommender systems: open issues, challenges, and techniques. Expert Syst Appl. 2023;213: 118823.","journal-title":"Expert Syst Appl"},{"key":"1173_CR44","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW.2013.33","volume-title":"Quantifying and recommending expertise when new skills emerge","author":"D Fang","year":"2013","unstructured":"Fang D, Varshney KR, Wang J, Ramamurthy KN, Mojsilovic A, Bauer JH. Quantifying and recommending expertise when new skills emerge. New York: IEEE; 2013."},{"key":"1173_CR45","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1016\/j.csi.2016.11.004","volume":"51","author":"L Fern\u00e1ndez-Sanz","year":"2017","unstructured":"Fern\u00e1ndez-Sanz L, G\u00f3mez-P\u00e9rez J, Castillo-Mart\u00ednez A. e-Skills Match: A framework for mapping and integrating the main skills, knowledge and competence standards and models for ICT occupations. Comput Stand Interf. 2017;51:30\u201342.","journal-title":"Comput Stand Interf"},{"issue":"9","key":"1173_CR46","doi-asserted-by":"publisher","first-page":"7645","DOI":"10.1016\/j.jksuci.2021.09.014","volume":"34","author":"F Fkih","year":"2022","unstructured":"Fkih F. Similarity measures for collaborative filtering-based recommender systems: review and experimental comparison. J King Saud Univ-Comput Inf Sci. 2022;34(9):7645\u201369.","journal-title":"J King Saud Univ-Comput Inf Sci"},{"issue":"1","key":"1173_CR47","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10115-020-01522-8","volume":"63","author":"MN Freire","year":"2021","unstructured":"Freire MN, de Castro LN. e-Recruitment recommender systems: a systematic review. Knowl Inf Syst. 2021;63(1):1\u201320.","journal-title":"Knowl Inf Syst"},{"key":"1173_CR48","first-page":"2349","volume":"2343","author":"F Fusco","year":"2019","unstructured":"Fusco F, Vlachos M, Vasileiadis V, Wardatzky K, Schneider J. RecoNet: an interpretable neural architecture for recommender systems. IJCAI. 2019;2343:2349.","journal-title":"IJCAI."},{"key":"1173_CR49","doi-asserted-by":"publisher","DOI":"10.1109\/BigData50022.2020.9377992","volume-title":"Skill-based career path modeling and recommendation","author":"A Ghosh","year":"2020","unstructured":"Ghosh A, Woolf B, Zilberstein S, Lan A. Skill-based career path modeling and recommendation. New York: IEEE; 2020."},{"key":"1173_CR50","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1145\/138859.138867","volume":"35","author":"D Goldberg","year":"1992","unstructured":"Goldberg D, Nichols D, Oki BM, Terry D. Using collaborative filtering to weave an information tapestry. Communi ACM. 1992;35:61\u201370. https:\/\/doi.org\/10.1145\/138859.138867.","journal-title":"Communi ACM"},{"key":"1173_CR51","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-94120-2_3","volume-title":"Case-based reasoning and agent-based job offer recommender system","author":"A Gonz\u00e1lez-Briones","year":"2019","unstructured":"Gonz\u00e1lez-Briones A, Rivas A, Chamoso P, Casado-Vara R, Corchado JM. Case-based reasoning and agent-based job offer recommender system. Cham: Springer International Publishing; 2019."},{"issue":"5","key":"1173_CR52","doi-asserted-by":"publisher","first-page":"599","DOI":"10.1111\/1475-3995.00376","volume":"9","author":"E Grigoroudis","year":"2002","unstructured":"Grigoroudis E, Politis Y, Siskos Y. Satisfaction benchmarking and customer classification: an application to the branches of a banking organization. Int Trans Oper Res. 2002;9(5):599\u2013618.","journal-title":"Int Trans Oper Res"},{"key":"1173_CR53","first-page":"12","volume":"10","author":"A Gunawardana","year":"2009","unstructured":"Gunawardana A, Shani G. A survey of accuracy evaluation metrics of recommendation tasks. J Machine Learn Res. 2009;10:12.","journal-title":"J Machine Learn Res"},{"key":"1173_CR54","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-0716-2197-4_15","volume-title":"Evaluating recommender systems","author":"A Gunawardana","year":"2022","unstructured":"Gunawardana A, Shani G, Yogev S. Evaluating recommender systems. New York, NY: Springer; 2022."},{"issue":"8","key":"1173_CR55","doi-asserted-by":"publisher","first-page":"3549","DOI":"10.1109\/TKDE.2020.3028705","volume":"34","author":"Q Guo","year":"2020","unstructured":"Guo Q, Zhuang F, Qin C, Zhu H, Xie X, Xiong H, He Q. A survey on knowledge graph-based recommender systems. IEEE Trans Knowl Data Eng. 2020;34(8):3549.","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"1173_CR56","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-13560-1_32","volume-title":"Combining career progression and profile matching in a job recommender system","author":"B Heap","year":"2014","unstructured":"Heap B, Krzywicki A, Wobcke W, Bain M, Compton P. Combining career progression and profile matching in a job recommender system. Cham: Springer International Publishing; 2014."},{"key":"1173_CR57","first-page":"100","volume":"91","author":"MHH Hisham","year":"2021","unstructured":"Hisham MHH, Aziz MA, Sulaiman AA. Job classification: a review on data, feature and methods. J Elect Elect Syst Res. 2021;91:100.","journal-title":"J Elect Elect Syst Res"},{"issue":"3","key":"1173_CR58","first-page":"261","volume":"16","author":"FO Isinkaye","year":"2015","unstructured":"Isinkaye FO, Folajimi YO, Ojokoh BA. Recommendation systems: principles, methods and evaluation. Egyp Inf J. 2015;16(3):261\u201373.","journal-title":"Egyp Inf J"},{"key":"1173_CR59","doi-asserted-by":"publisher","DOI":"10.1109\/CONFLUENCE.2019.8776964","volume-title":"Job recommendation system based on machine learning and data mining techniques using RESTful API and android IDE","author":"H Jain","year":"2019","unstructured":"Jain H, Kakkar M. Job recommendation system based on machine learning and data mining techniques using RESTful API and android IDE. New York: IEEE; 2019."},{"key":"1173_CR60","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-91476-3_42","volume-title":"How to match jobs and candidates-a recruitment support system based on feature engineering and advanced analytics","author":"A Janusz","year":"2018","unstructured":"Janusz A, Stawicki S, Drewniak M, Ciebiera K, \u015al\u0119zak D, Stencel K. How to match jobs and candidates-a recruitment support system based on feature engineering and advanced analytics. New York: Springer International Publishing; 2018."},{"key":"1173_CR61","doi-asserted-by":"publisher","DOI":"10.1109\/WETICE.2017.8","volume-title":"Interoperability and scalability for worker-job matching across crowdsourcing platforms","author":"J Jarrett","year":"2017","unstructured":"Jarrett J, Blake MB. Interoperability and scalability for worker-job matching across crowdsourcing platforms. New York: IEEE; 2017."},{"issue":"3\/4","key":"1173_CR62","doi-asserted-by":"publisher","first-page":"214","DOI":"10.1108\/EJTD-05-2018-0045","volume":"43","author":"B Ju","year":"2019","unstructured":"Ju B, Li J. Exploring the impact of training, job tenure, and education-job and skills-job matches on employee turnover intention. Euro J Train Dev. 2019;43(3\/4):214\u201331.","journal-title":"Euro J Train Dev"},{"issue":"20","key":"1173_CR63","doi-asserted-by":"publisher","first-page":"4284","DOI":"10.3390\/app9204284","volume":"9","author":"JS Kang","year":"2019","unstructured":"Kang JS, Shin DH, Baek JW, Chung K. Activity recommendation model using rank correlation for chronic stress management. Appl Sci. 2019;9(20):4284.","journal-title":"Appl Sci"},{"issue":"4","key":"1173_CR64","first-page":"82","volume":"1","author":"AS Kapse","year":"2012","unstructured":"Kapse AS, Patil VS, Patil NV. E-recruitment. Int J Eng Adv Technol. 2012;1(4):82\u20136.","journal-title":"Int J Eng Adv Technol"},{"issue":"4","key":"1173_CR65","first-page":"1","volume":"2","author":"U Karaboga","year":"2020","unstructured":"Karaboga U, Vardarlier P. Examining the use of artificial intelligence in recruitment processes. Bussecon Rev Soc Sci. 2020;2(4):1\u201317.","journal-title":"Bussecon Rev Soc Sci"},{"key":"1173_CR66","doi-asserted-by":"publisher","DOI":"10.5120\/15279-4033","author":"R Kumar","year":"2014","unstructured":"Kumar R, Verma BK, Rastogi SS. Social popularity based SVD++ recommender system. Int J Comput Applic. 2014. https:\/\/doi.org\/10.5120\/15279-4033.","journal-title":"Int J Comput Applic"},{"key":"1173_CR67","doi-asserted-by":"publisher","first-page":"20553","DOI":"10.1109\/ACCESS.2023.3249356","volume":"11","author":"R Kwieci\u0144ski","year":"2023","unstructured":"Kwieci\u0144ski R, Melniczak G, G\u00f3recki T. Comparison of real-time and batch job recommendations. IEEE Access. 2023;11:20553\u20139.","journal-title":"IEEE Access"},{"key":"1173_CR68","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-28238-6_38","volume-title":"Joint extraction and classification of danish competences for job matching","author":"Q Li","year":"2023","unstructured":"Li Q, Lioma C. Joint extraction and classification of danish competences for job matching. Cham: Springer Nature Switzerland; 2023."},{"key":"1173_CR69","doi-asserted-by":"publisher","DOI":"10.1155\/2022\/9245876","author":"F Liang","year":"2022","unstructured":"Liang F, Wan X. Job matching analysis based on text mining and multicriteria decision-making. Math Problems Eng. 2022. https:\/\/doi.org\/10.1155\/2022\/9245876.","journal-title":"Math Problems Eng"},{"issue":"2","key":"1173_CR70","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3678004","volume":"43","author":"J Lin","year":"2023","unstructured":"Lin J, Dai X, Xi Y, Liu W, Chen B, Zhang H, Zhang W. How can recommender systems benefit from large language models: A survey. ACM Trans Inf Syst. 2023;43(2):1\u201347.","journal-title":"ACM Trans Inf Syst"},{"key":"1173_CR71","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-45817-5_12","volume-title":"A context-aware method for top-k recommendation in smart TV","author":"P Liu","year":"2016","unstructured":"Liu P, Ma J, Wang Y, Ma L, Huang S. A context-aware method for top-k recommendation in smart TV. Cham: Springer; 2016."},{"issue":"1","key":"1173_CR72","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.physrep.2012.02.006","volume":"519","author":"L L\u00fc","year":"2012","unstructured":"L\u00fc L, Medo M, Yeung CH, Zhang YC, Zhang ZK, Zhou T. Recommender systems. Phys Rep. 2012;519(1):1\u201349.","journal-title":"Phys Rep"},{"key":"1173_CR73","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1016\/j.dss.2015.03.008","volume":"74","author":"J Lu","year":"2015","unstructured":"Lu J, Wu D, Mao M, Wang W, Zhang G. Recommender system application developments: a survey. Decis Support Syst. 2015;74:12\u201332.","journal-title":"Decis Support Syst"},{"key":"1173_CR74","doi-asserted-by":"publisher","DOI":"10.1109\/ES.2014.16","volume-title":"A hybrid user profile model for personalized recommender system with linked open data","author":"Y Luo","year":"2014","unstructured":"Luo Y, Xu B, Cai H, Bu F. A hybrid user profile model for personalized recommender system with linked open data. New York: IEEE; 2014."},{"issue":"6","key":"1173_CR75","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1108\/14754391111172788","volume":"10","author":"SA Madia","year":"2011","unstructured":"Madia SA. Best practices for using social media as a recruitment strategy. Strateg HR Rev. 2011;10(6):19\u201324.","journal-title":"Strateg HR Rev"},{"key":"1173_CR76","doi-asserted-by":"publisher","DOI":"10.1109\/ASONAM.2014.6921646","volume-title":"Field selection for job categorization and recommendation to social network users","author":"E Malherbe","year":"2014","unstructured":"Malherbe E, Diaby M, Cataldi M, Viennet E, Aufaure MA. Field selection for job categorization and recommendation to social network users. New York: IEEE; 2014."},{"key":"1173_CR77","first-page":"274","volume":"22","author":"AN Marlowe","year":"2021","unstructured":"Marlowe AN. Robot recruiters: how employers & governments must confront the discriminatory effects of AI hiring. J High Tech L. 2021;22:274.","journal-title":"J High Tech L"},{"issue":"3","key":"1173_CR78","first-page":"19","volume":"32","author":"FJ Martin","year":"2011","unstructured":"Martin FJ, Donaldson J, Ashenfelter A, Torrens M, Hangartner R. The big promise of recommender systems. AI Mag. 2011;32(3):19\u201327.","journal-title":"AI Mag"},{"issue":"6","key":"1173_CR79","doi-asserted-by":"publisher","first-page":"1265","DOI":"10.1007\/s10796-019-09929-7","volume":"22","author":"J Martinez-Gil","year":"2020","unstructured":"Martinez-Gil J, Paoletti AL, Pichler M. A novel approach for learning how to automatically match job offers and candidate profiles. Inf Syst Front. 2020;22(6):1265\u201374.","journal-title":"Inf Syst Front"},{"key":"1173_CR80","doi-asserted-by":"publisher","DOI":"10.1109\/GC46384.2019.00020","volume-title":"A graph-based recommender system for food products","author":"A Mathur","year":"2019","unstructured":"Mathur A, Juguru SK, Eirinaki M. A graph-based recommender system for food products. New York: IEEE; 2019."},{"key":"1173_CR81","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2017.8258045","volume-title":"Bayesian multi-view models for member-job matching and personalized skill recommendations","author":"A Maurya","year":"2017","unstructured":"Maurya A, Telang R. Bayesian multi-view models for member-job matching and personalized skill recommendations. New York: IEEE; 2017."},{"issue":"1","key":"1173_CR82","first-page":"31","volume":"20","author":"Y Melanthiou","year":"2015","unstructured":"Melanthiou Y, Pavlou F, Constantinou E. The use of social network sites as an e-recruitment tool. J Trans Manag. 2015;20(1):31\u201349.","journal-title":"J Trans Manag"},{"issue":"2006","key":"1173_CR83","first-page":"775","volume":"6","author":"R Mihalcea","year":"2006","unstructured":"Mihalcea R, Corley C, Strapparava C. Corpus-based and knowledge-based measures of text semantic similarity. Aaai. 2006;6(2006):775\u201380.","journal-title":"Aaai"},{"key":"1173_CR84","doi-asserted-by":"publisher","DOI":"10.1109\/ICTSD.2015.7095894","volume-title":"Generating personalized job role recommendations for the IT sector through predictive analytics and personality traits","author":"IA Mirza","year":"2015","unstructured":"Mirza IA, Mulla S, Parekh R, Sawant S, Singh KM. Generating personalized job role recommendations for the IT sector through predictive analytics and personality traits. New York: IEEE; 2015."},{"key":"1173_CR85","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-15-1420-3_91","volume-title":"Efficient and scalable job recommender system using collaborative filtering","author":"R Mishra","year":"2020","unstructured":"Mishra R, Rathi S. Efficient and scalable job recommender system using collaborative filtering. Singapore: Springer Singapore; 2020."},{"key":"1173_CR86","doi-asserted-by":"publisher","DOI":"10.1109\/ITCE.2019.8646645","volume-title":"Recommender systems challenges and solutions survey","author":"MH Mohamed","year":"2019","unstructured":"Mohamed MH, Khafagy MH, Ibrahim MH. Recommender systems challenges and solutions survey. New York: IEEE; 2019."},{"key":"1173_CR87","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/8269.001.0001","volume-title":"The architecture machine: toward a more human environment","author":"N Negroponte","year":"1970","unstructured":"Negroponte N. The architecture machine: toward a more human environment. The MIT Press; 1970."},{"key":"1173_CR88","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-00293-4_21","volume-title":"Supporting career counseling with user modeling and job matching","author":"CD Nguyen","year":"2013","unstructured":"Nguyen CD, Vo KD, Nguyen DT. Supporting career counseling with user modeling and job matching. Cham: Springer International Publishing; 2013."},{"key":"1173_CR89","volume-title":"Job training recommendation system: integrated fuzzy AHP and TOPSIS approach","author":"Okfalisa","year":"2021","unstructured":"Okfalisa, Siburian R, Vitriani Y, Rusnedy H. Job training recommendation system: integrated fuzzy AHP and TOPSIS approach. Cham: Springer International Publishing; 2021."},{"key":"1173_CR90","doi-asserted-by":"publisher","DOI":"10.1109\/ICCSS.2014.6961826","volume-title":"A model to forecast the matched-degree between staffs and jobs","author":"Y Ouyang","year":"2014","unstructured":"Ouyang Y, Mo H, Peng F, Tan D. A model to forecast the matched-degree between staffs and jobs. New York: IEEE; 2014."},{"key":"1173_CR91","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT.2018.8437786","volume-title":"On the universality of the logistic loss function","author":"A Painsky","year":"2018","unstructured":"Painsky A, Wornell G. On the universality of the logistic loss function. New York: IEEE; 2018."},{"key":"1173_CR92","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1016\/j.inffus.2020.12.001","volume":"69","author":"I Palomares","year":"2021","unstructured":"Palomares I, Porcel C, Pizzato L, Guy I, Herrera-Viedma E. Reciprocal Recommender Systems: Analysis of state-of-art literature, challenges and opportunities towards social recommendation. Information Fusion. 2021;69:103\u201327.","journal-title":"Information Fusion"},{"key":"1173_CR93","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-45817-5_55","volume-title":"Combo-Recommendation Based on Potential Relevance of Items","author":"Y Pan","year":"2016","unstructured":"Pan Y, Zhang Y, Zhang R. Combo-Recommendation Based on Potential Relevance of Items. Cham: Springer; 2016."},{"issue":"1","key":"1173_CR94","first-page":"16","volume":"14","author":"U Paral\u0131","year":"2019","unstructured":"Paral\u0131 U, Zontul M, Ertu\u011frul D\u00c7. Information retrieval using the reduced row echelon form of a term-document matrix. J Int Technol. 2019;14(1):16\u201328.","journal-title":"J Int Technol"},{"issue":"11","key":"1173_CR95","doi-asserted-by":"publisher","first-page":"10059","DOI":"10.1016\/j.eswa.2012.02.038","volume":"39","author":"DH Park","year":"2012","unstructured":"Park DH, Kim HK, Choi IY, Kim JK. A literature review and classification of recommender systems research. Expert Syst Appl. 2012;39(11):10059\u201372.","journal-title":"Expert Syst Appl"},{"key":"1173_CR96","doi-asserted-by":"publisher","DOI":"10.1109\/ICSCDS56580.2023.10104718","volume-title":"A survey on artificial intelligence (AI) based job recommendation systems","author":"A Patil","year":"2023","unstructured":"Patil A, Suwalka D, Kumar A, Rai G, Saha J. A survey on artificial intelligence (AI) based job recommendation systems. New York: IEEE; 2023."},{"issue":"9","key":"1173_CR97","first-page":"22","volume":"6","author":"A Poriya","year":"2014","unstructured":"Poriya A, Bhagat T, Patel N, Sharma R. Non-personalized recommender systems and user-based collaborative recommender systems. Int J Appl Inf Syst. 2014;6(9):22\u20137.","journal-title":"Int J Appl Inf Syst"},{"key":"1173_CR98","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1016\/j.eswa.2017.12.020","volume":"97","author":"I Portugal","year":"2018","unstructured":"Portugal I, Alencar P, Cowan D. The use of machine learning algorithms in recommender systems: a systematic review. Expert Syst Appl. 2018;97:205\u201327.","journal-title":"Expert Syst Appl"},{"key":"1173_CR99","doi-asserted-by":"publisher","DOI":"10.1109\/GECOST55694.2022.10010659","volume-title":"Multiclass job recommendation system in the IT field between classification and prediction method","author":"KN Prafajar","year":"2022","unstructured":"Prafajar KN, Vallyan H, Candradewi NLPA, Edbert IS, Suhartono D. Multiclass job recommendation system in the IT field between classification and prediction method. New York: IEEE; 2022."},{"issue":"7","key":"1173_CR100","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.1000097","volume":"6","author":"PRISMA Preferred Reporting Items for Systematic Reviews and Meta-Analyses","year":"2009","unstructured":"PRISMA Preferred Reporting Items for Systematic Reviews and Meta-Analyses. PRISMA Statement. PLOS Med. 2009;6(7): e1000097. https:\/\/doi.org\/10.1371\/journal.pmed.1000097.","journal-title":"PLOS Med"},{"key":"1173_CR101","volume-title":"Semantic matching strategies for job recruitment: A comparison of new and known approaches","author":"G R\u00e1cz","year":"2016","unstructured":"R\u00e1cz G, Sali A, Schewe KD. Semantic matching strategies for job recruitment: A comparison of new and known approaches. Cham: Springer International Publishing; 2016."},{"key":"1173_CR102","doi-asserted-by":"publisher","DOI":"10.1109\/ICInPro47689.2019.9092271","volume-title":"Improving job recommendation using ontological modeling and user profiles","author":"SR Rimitha","year":"2019","unstructured":"Rimitha SR, Abburu V, Kiranmai A, Marimuthu C, Chandrasekaran K. Improving job recommendation using ontological modeling and user profiles. New York: IEEE; 2019."},{"key":"1173_CR103","doi-asserted-by":"publisher","DOI":"10.1109\/EDUCON.2019.8725258","volume-title":"Engineering solutions on multimodal profiling tool for digital jobs analysis and matching of requirements competences frameworks","author":"D Rutkauskiene","year":"2019","unstructured":"Rutkauskiene D, Gudoniene D. Engineering solutions on multimodal profiling tool for digital jobs analysis and matching of requirements competences frameworks. New York: IEEE; 2019."},{"key":"1173_CR104","doi-asserted-by":"publisher","DOI":"10.1109\/WI-IAT55865.2022.00011","volume-title":"Job recommendation based on multiple behaviors and explicit preferences","author":"Y Saito","year":"2022","unstructured":"Saito Y, Sugiyama K. Job recommendation based on multiple behaviors and explicit preferences. New York: IEEE; 2022."},{"key":"1173_CR105","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-19033-4_34","volume-title":"A case-based multi-agent and recommendation environment to improve the e-recruitment process","author":"OM Salazar","year":"2015","unstructured":"Salazar OM, Jaramillo JC, Ovalle DA, Guzm\u00e1n JA. A case-based multi-agent and recommendation environment to improve the e-recruitment process. Cham: Springer International Publishing; 2015."},{"key":"1173_CR106","volume-title":"Term weighting approaches in automatic text retrieval. In Readings in Information Retrieval","author":"G Salton","year":"1997","unstructured":"Salton G, Buckley C. Term weighting approaches in automatic text retrieval. In Readings in Information Retrieval. San Francisco, CA: Morgan Kaufmann Publishers; 1997."},{"key":"1173_CR107","volume-title":"Computer evaluation of indexing and text processing","author":"G Salton","year":"1971","unstructured":"Salton G, Lesk M. Computer evaluation of indexing and text processing. Englewood Cliffs New Jersey: Prentice Hall Ing; 1971."},{"issue":"2","key":"1173_CR108","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1016\/S0306-4573(96)00062-3","volume":"33","author":"G Salton","year":"1997","unstructured":"Salton G, Singhal A, Mitra M, Buckley C. Automatic text structuring and summarization. Inf Process Manage. 1997;33(2):193\u2013207.","journal-title":"Inf Process Manage"},{"key":"1173_CR109","doi-asserted-by":"publisher","DOI":"10.1109\/CONFLUENCE.2018.8442697","volume-title":"A novel singularity based improved Tanimoto similarity measure for effective recommendation using collaborative filtering","author":"C Selvi","year":"2018","unstructured":"Selvi C, Sivasankar E. A novel singularity based improved Tanimoto similarity measure for effective recommendation using collaborative filtering. New York: IEEE; 2018."},{"key":"1173_CR110","doi-asserted-by":"publisher","DOI":"10.1109\/EIConRus.2017.7910613","volume-title":"Collaborative filtering for music recommender system","author":"E Shakirova","year":"2017","unstructured":"Shakirova E. Collaborative filtering for music recommender system. New York: IEEE; 2017."},{"key":"1173_CR111","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-85820-3_8","volume-title":"Evaluating recommendation systems","author":"G Shani","year":"2011","unstructured":"Shani G, Gunawardana A. Evaluating recommendation systems. Boston, MA: Springer; 2011."},{"issue":"5","key":"1173_CR112","doi-asserted-by":"publisher","first-page":"813","DOI":"10.1007\/s13042-017-0762-9","volume":"10","author":"T Silveira","year":"2019","unstructured":"Silveira T, Zhang M, Lin X, Liu Y, Ma S. How good your recommender system is? A survey on evaluations in recommendation. Int J Mach Learn Cybern. 2019;10(5):813\u201331.","journal-title":"Int J Mach Learn Cybern"},{"key":"1173_CR113","volume-title":"Job recommender systems: a survey","author":"Z Siting","year":"2012","unstructured":"Siting Z, Wenxing H, Ning Z, Fan Y. Job recommender systems: a survey. New York: IEEE; 2012."},{"issue":"1904","key":"1173_CR114","first-page":"72","volume":"15","author":"C Spearman","year":"1961","unstructured":"Spearman C. The proof and measurement of association between two things. Am J Psychol. 1961;15(1904):72\u2013101.","journal-title":"Am J Psychol"},{"issue":"2","key":"1173_CR115","first-page":"139","volume":"25","author":"DL Stone","year":"2015","unstructured":"Stone DL, Deadrick DL. Challenges and opportunities affecting the future of human resource management. Hum Resour Manag Rev. 2015;25(2):139\u201345.","journal-title":"Hum Resour Manag Rev"},{"key":"1173_CR116","volume-title":"Dataops for societal intelligence: a data pipeline for labor market skills extraction and matching","author":"DA Tamburri","year":"2020","unstructured":"Tamburri DA, Van Den Heuvel WJ, Garriga M. Dataops for societal intelligence: a data pipeline for labor market skills extraction and matching. New York: IEEE; 2020."},{"issue":"2","key":"1173_CR117","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10676-022-09633-2","volume":"24","author":"N Tilmes","year":"2022","unstructured":"Tilmes N. Disability, fairness, and algorithmic bias in AI recruitment. Ethics Inf Technol. 2022;24(2):1\u201313.","journal-title":"Ethics Inf Technol"},{"key":"1173_CR118","volume-title":"Review of job recommender system using big data analytics","author":"P Tripathi","year":"2016","unstructured":"Tripathi P, Agarwal R, Vashishtha T. Review of job recommender system using big data analytics. New York: IEEE; 2016."},{"key":"1173_CR119","doi-asserted-by":"publisher","DOI":"10.1109\/SMC52423.2021.9658757","volume-title":"Explainable job-posting recommendations using knowledge graphs and named entity recognition","author":"C Upadhyay","year":"2021","unstructured":"Upadhyay C, Abu-Rasheed H, Weber C, Fathi M. Explainable job-posting recommendations using knowledge graphs and named entity recognition. New York: IEEE; 2021."},{"key":"1173_CR120","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-29739-8_17","volume-title":"Use of artificial intelligence as business strategy in recruitment process and social perspective","author":"P Vardarlier","year":"2020","unstructured":"Vardarlier P, Zafer C. Use of artificial intelligence as business strategy in recruitment process and social perspective. Cham: Springer; 2020."},{"issue":"6","key":"1173_CR121","doi-asserted-by":"publisher","first-page":"1237","DOI":"10.1080\/09585192.2020.1871398","volume":"33","author":"D Vrontis","year":"2022","unstructured":"Vrontis D, Christofi M, Pereira V, Tarba S, Makrides A, Trichina E. Artificial intelligence, robotics, advanced technologies and human resource management: a systematic review. Int J Human Res Manag. 2022;33(6):1237\u201366.","journal-title":"Int J Human Res Manag"},{"key":"1173_CR122","volume-title":"A trustworthy and explainable AI recommender system: job domain case study","author":"A Vultureanu-Albi\u015fi","year":"2024","unstructured":"Vultureanu-Albi\u015fi A, Murare\u0163u I, B\u0103dic\u0103 C. A trustworthy and explainable AI recommender system: job domain case study. New York: IEEE; 2024."},{"key":"1173_CR123","volume-title":"The analysis and design of the job recommendation model based on GBRT and time factors","author":"P Wang","year":"2016","unstructured":"Wang P, Dou Y, Xin Y. The analysis and design of the job recommendation model based on GBRT and time factors. New York: IEEE; 2016."},{"key":"1173_CR124","volume-title":"iHR+: A mobile reciprocal job recommender system","author":"H Wenxing","year":"2015","unstructured":"Wenxing H, Yiwei C, Jianwei Q, Yin H. iHR+: A mobile reciprocal job recommender system. New York: IEEE; 2015."},{"key":"1173_CR125","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-45817-5_5","volume-title":"Real-time anomaly detection over ECG data stream based on component spectrum","author":"M Wu","year":"2016","unstructured":"Wu M, Qiu Z, Hong S, Li H. Real-time anomaly detection over ECG data stream based on component spectrum. Cham: Springer; 2016."},{"issue":"5","key":"1173_CR126","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3535101","volume":"55","author":"S Wu","year":"2022","unstructured":"Wu S, Sun F, Zhang W, Xie X, Cui B. Graph neural networks in recommender systems: a survey. ACM Comput Surv. 2022;55(5):1\u201337.","journal-title":"ACM Comput Surv"},{"issue":"8","key":"1173_CR127","first-page":"9178","volume":"38","author":"L Wu","year":"2024","unstructured":"Wu L, Qiu Z, Zheng Z, Zhu H, Chen E. Exploring large language model for graph data understanding in online job recommendations. Proc AAAI Conf Artif Intell. 2024;38(8):9178\u201386.","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"1173_CR128","volume-title":"FHSM: factored hybrid similarity methods for top-n recommender systems","author":"X Xin","year":"2016","unstructured":"Xin X, Wang D, Ding Y, Lini C. FHSM: factored hybrid similarity methods for top-n recommender systems. Cham: Springer; 2016."},{"key":"1173_CR129","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1016\/j.knosys.2017.08.017","volume":"136","author":"S Yang","year":"2017","unstructured":"Yang S, Korayem M, AlJadda K, Grainger T, Natarajan S. Combining content-based and collaborative filtering for job recommendation system: a cost-sensitive Statistical Relational Learning approach. Knowl-Based Syst. 2017;136:37\u201345.","journal-title":"Knowl-Based Syst"},{"issue":"1","key":"1173_CR130","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-020-79139-8","volume":"11","author":"Q Yang","year":"2021","unstructured":"Yang Q, You X, Zhang Y. Two-sided matching based on I-BTM and LSGDM applied to high-level overseas talent and job fit problems. Sci Rep. 2021;11(1):1\u201322.","journal-title":"Sci Rep"},{"issue":"2","key":"1173_CR131","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1002\/(SICI)1097-4571(199503)46:2<133::AID-ASI6>3.0.CO;2-Z","volume":"46","author":"YY Yao","year":"1995","unstructured":"Yao YY. Measuring retrieval effectiveness based on user preference of documents. J Am Soc Inf Sci. 1995;46(2):133\u201345.","journal-title":"J Am Soc Inf Sci"},{"key":"1173_CR132","volume-title":"A job recommendation method optimized by position descriptions and resume information","author":"P Yi","year":"2016","unstructured":"Yi P, Yang C, Li C, Zhang Y. A job recommendation method optimized by position descriptions and resume information. New York: IEEE; 2016."},{"issue":"16","key":"1173_CR133","first-page":"4061","volume":"8","author":"H Yu","year":"2011","unstructured":"Yu H, Liu C, Zhang F. Reciprocal recommendation algorithm for the field of recruitment. J Inf Comput Sci. 2011;8(16):4061\u20138.","journal-title":"J Inf Comput Sci"},{"key":"1173_CR134","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-45817-5_14","volume-title":"Improving temporal recommendation accuracy and diversity via long and short-term preference transfer and fusion models","author":"B Zhang","year":"2016","unstructured":"Zhang B, Feng Y. Improving temporal recommendation accuracy and diversity via long and short-term preference transfer and fusion models. Cham: Springer; 2016."},{"key":"1173_CR135","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2024.3392335","author":"Z Zhao","year":"2024","unstructured":"Zhao Z, Fan W, Li J, Liu Y, Mei X, Wang Y, Li Q. Recommender systems in the era of large language models (llms). IEEE Trans Knowl Data Eng. 2024. https:\/\/doi.org\/10.1109\/TKDE.2024.3392335.","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"1173_CR136","doi-asserted-by":"crossref","unstructured":"Arita S, Hiyama A, Hirose M. Gber: a social matching app which utilizes time, place, and skills of workers and jobs. In&nbsp;Companion of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing. 2017","DOI":"10.1145\/3022198.3026316"},{"key":"1173_CR137","doi-asserted-by":"crossref","unstructured":"Borisyuk F, Zhang L, Kenthapadi K. LiJAR: A system for job application redistribution towards efficient career marketplace. In&nbsp;Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2017","DOI":"10.1145\/3097983.3098028"},{"key":"1173_CR138","unstructured":"Brek A, Boufaida Z. Semantic Approaches Survey for Job Recommender Systems. 2020."},{"key":"1173_CR139","doi-asserted-by":"crossref","unstructured":"Chuang, S. Indispensable skills for human employees in the age of robots and AI.&nbsp;European Journal of Training and Development, (ahead-of-print). 2022.","DOI":"10.1108\/EJTD-06-2022-0062"},{"key":"1173_CR140","doi-asserted-by":"crossref","unstructured":"Dave VS, Zhang B, Al Hasan M, AlJadda K, Korayem MA combined representation learning approach for better job and skill recommendation. In&nbsp;Proceedings of the 27th ACM International Conference on Information and Knowledge Management&nbsp;(pp. 1997\u20132005). 2018.","DOI":"10.1145\/3269206.3272023"},{"key":"1173_CR141","unstructured":"De Ruijt C, Bhulai S. Job recommender systems: A review.&nbsp;arXiv preprint arXiv:2111.13576. 2021."},{"key":"1173_CR142","unstructured":"DISCO Tool (2012). European Dictionary of Skills and Competences Structured&nbsp;Vocabulary, Retrieved from: http:\/\/www.disco-tools.eu, Accessed 28.11.2023"},{"key":"1173_CR143","unstructured":"ESCO Portal (2010). A Multilingual Classification on European Skills, Competences, Qualifications and Occupations Classification Tool, developed by&nbsp;The European Commission, Retrieved from: https:\/\/ec.europa.eu\/social\/home.jsp?langId=en, Accessed 28.11.2023."},{"key":"1173_CR144","doi-asserted-by":"crossref","unstructured":"Guan Z, Yu B, Liu Y. Recruitment and recommendation system based on intelligent computing. In&nbsp;Proceedings of the 2019 5th International Conference on Computing and Data Engineering. 2019","DOI":"10.1145\/3330530.3330532"},{"key":"1173_CR145","doi-asserted-by":"crossref","unstructured":"Guti\u00e9rrez F, Charleer S, De Croon R, Htun NN, Goetschalckx G, Verbert K. Explaining and exploring job recommendations: a user-driven approach for interacting with knowledge-based job recommender systems. In&nbsp;Proceedings of the 13th ACM Conference on Recommender Systems. 2019","DOI":"10.1145\/3298689.3347001"},{"key":"1173_CR146","unstructured":"HRCI, Human Resources Certification Institute (1973), https:\/\/www.hrci.org\/, Accessed 28.11.2023"},{"key":"1173_CR147","unstructured":"ISCED A Statistical Framework on International Standard Classification of Education, maintained by the United Nations Educational, Scientific and Cultural Organization (UNESCO), (2011). http:\/\/www.uis.unesco.org\/Education\/Pages\/international-standard-classification-of-education.aspx, Accessed 28.11.2023"},{"key":"1173_CR148","unstructured":"ISCO Tool (2008). International Standard Classification of Occupations Tool, Retrieved from: https:\/\/www.ilo.org\/public\/english\/bureau\/stat\/isco\/isco88\/alpha.htm, Accessed 28.11.2023"},{"key":"1173_CR149","doi-asserted-by":"crossref","unstructured":"Kenthapadi K, Le B. Venkataraman G. Personalized job recommendation system at linkedin: Practical challenges and lessons learned. In&nbsp;Proceedings of the eleventh ACM conference on recommender systems. 2017","DOI":"10.1145\/3109859.3109921"},{"key":"1173_CR150","doi-asserted-by":"crossref","unstructured":"Li L, Li T.. MEET: a generalized framework for reciprocal recommender systems. In&nbsp;Proceedings of the 21st ACM international conference on Information and knowledge management&nbsp;(pp. 35\u201344). 2012.","DOI":"10.1145\/2396761.2396770"},{"key":"1173_CR151","doi-asserted-by":"crossref","unstructured":"Li S, Shi B, Yang J, Yan J, Wang S, Chen F, He Q. Deep job understanding at linkedin. In&nbsp;Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. 2020.","DOI":"10.1145\/3397271.3401403"},{"key":"1173_CR152","doi-asserted-by":"crossref","unstructured":"Lu Y, El Helou S, Gillet DA recommender system for job seeking and recruiting website. In&nbsp;Proceedings of the 22nd International Conference on World Wide Web. 2013.","DOI":"10.1145\/2487788.2488092"},{"key":"1173_CR153","unstructured":"McFee B, Lanckriet GR. Metric learning to rank. In&nbsp;Proceedings of the 27th international conference on machine learning (ICML-10)&nbsp;(pp. 775\u2013782). 2010."},{"key":"1173_CR154","unstructured":"Nimmakayala, S., Korada, J., Mamidi, G., Naik, K. S. S., & Anusha, C. Natural Language Processing Bots For Job Searching Integrated With The Job Recommendation System And Notification Alerting System, Dogo Rangsang Research Journal, ISSN : 2347\u20137180, Vol. 12 Issue-08 No. 04 August 2022. 2022"},{"key":"1173_CR155","doi-asserted-by":"crossref","unstructured":"Ortega A, Fierrez J, Morales A, Wang Z, Ribeiro T. Symbolic AI for XAI: Evaluating LFIT inductive programming for fair and explainable automatic recruitment. In&nbsp;Proceedings of the IEEE\/CVF winter conference on applications of computer vision. 2021.","DOI":"10.1109\/WACVW52041.2021.00013"},{"key":"1173_CR156","unstructured":"Roberts, J. Introducing RAI:The First AI Assistant for Recruiters, 2016 https:\/\/hiringsolved.com\/, Accessed 13 01 2023."},{"key":"1173_CR157","doi-asserted-by":"crossref","unstructured":"Schellingerhout, R. Explainable multi-stakeholder job recommender systems. In&nbsp;Proceedings of the 18th ACM Conference on Recommender Systems. 2024","DOI":"10.1145\/3640457.3688014"},{"key":"1173_CR158","unstructured":"Schr\u00f6der G, Thiele M, Lehner W Setting goals and choosing metrics for recommender system evaluations. UCERSTI2 workshop at the 5th ACM conference on recommender systems, Chicago USA. 23: 53. 2011"},{"key":"1173_CR159","unstructured":"Shervin Minaee. 20 Popular Machine Learning Metrics. Part 2: Ranking, & Statistical Metrics, 2020. https:\/\/towardsdatascience.com\/20-popular-machine-learning-metrics-part-2-ranking-statistical-metrics-22c3e5a937b6, Accessed 13 01 2023."},{"key":"1173_CR160","doi-asserted-by":"crossref","unstructured":"Sun Y, Zhuang F, Zhu H, He Q, Xiong H. Cost-effective and interpretable job skill recommendation with deep reinforcement learning. In&nbsp;Proceedings of the Web Conference 2021. 2021.","DOI":"10.1145\/3442381.3449985"},{"key":"1173_CR161","unstructured":"Vats A, Jain V, Raja R, Chadha A. Exploring the impact of large language models on recommender systems: an extensive review.&nbsp;arXiv preprint arXiv:2402.18590. 2024."},{"key":"1173_CR162","unstructured":"Vijaysinh L. How to Measure the Success of a Recommendation System?, in Developers Corner, October 24, 2021 https:\/\/analyticsindiamag.com\/how-to-measure-the-success-of-a-recommendation-system\/, Accessed 13 01 2023."},{"key":"1173_CR163","unstructured":"Wang, B. Ranking Evaluation Metrics for Recommender Systems, Towards Data Science, Jan 18, 2021, 2021. https:\/\/towardsdatascience.com\/ranking-evaluation-metrics-for-recommender-systems-263d0a66ef54, Accessed 13 01 2023."},{"key":"1173_CR164","unstructured":"Webb, A. Mya Systems, MYA, Industry\u2019s Leading Conversational AI Recruiter, Takes Market by Storm, Adds 120 Enterprise Customers, Including 40 of&nbsp;Fortune&nbsp;500, in Under Two Years, 2018. https:\/\/www.businesswire.com\/news\/home\/20180828005301\/en\/Mya-Industry%E2%80%99s-Leading-Conversational-AI-Recruiter-Takes-Market-by-Storm-Adds-120-Enterprise-Customers-Including-40-of-Fortune-500-in-Under-Two-Years, Accessed 13 01 2023."},{"key":"1173_CR165","doi-asserted-by":"crossref","unstructured":"Zhao T, Wuyu C, Zhixiang C. Summer Job selection model based on job matching and comprehensive evaluation algorithm. In&nbsp;2021 2nd International Conference on Artificial Intelligence and Information Systems. 2021","DOI":"10.1145\/3469213.3470394"}],"container-title":["Journal of Big Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s40537-025-01173-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s40537-025-01173-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s40537-025-01173-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,2]],"date-time":"2025-06-02T08:03:06Z","timestamp":1748851386000},"score":1,"resource":{"primary":{"URL":"https:\/\/journalofbigdata.springeropen.com\/articles\/10.1186\/s40537-025-01173-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,2]]},"references-count":165,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["1173"],"URL":"https:\/\/doi.org\/10.1186\/s40537-025-01173-y","relation":{},"ISSN":["2196-1115"],"issn-type":[{"value":"2196-1115","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6,2]]},"assertion":[{"value":"15 January 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 April 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 June 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":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"The authors declare no competing interests.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"140"}}