{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T01:11:54Z","timestamp":1772500314975,"version":"3.50.1"},"reference-count":40,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2024,8,20]],"date-time":"2024-08-20T00:00:00Z","timestamp":1724112000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>In the continuously changing labor market, understanding the dynamics of online job postings is crucial for economic and workforce development. With the increasing reliance on Online Job Portals, analyzing online job postings has become an essential tool for capturing real-time labor-market trends. This paper presents a comprehensive methodology for processing online job postings to generate labor-market intelligence. The proposed methodology encompasses data source selection, data extraction, cleansing, normalization, and deduplication procedures. The final step involves information extraction based on employer industry, occupation, workplace, skills, and required experience. We address the key challenges that emerge at each step and discuss how they can be resolved. Our methodology is applied to two use cases: the first focuses on the analysis of the Greek labor market in the tourism industry during the COVID-19 pandemic, revealing shifts in job demands, skill requirements, and employment types. In the second use case, a data-driven ontology is employed to extract skills from job postings using machine learning. The findings highlight that the proposed methodology, utilizing NLP and machine-learning techniques instead of LLMs, can be applied to different labor market-analysis use cases and offer valuable insights for businesses, job seekers, and policymakers.<\/jats:p>","DOI":"10.3390\/info15080496","type":"journal-article","created":{"date-parts":[[2024,8,20]],"date-time":"2024-08-20T01:38:45Z","timestamp":1724117925000},"page":"496","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["From Data to Insight: Transforming Online Job Postings into Labor-Market Intelligence"],"prefix":"10.3390","volume":"15","author":[{"given":"Giannis","family":"Tzimas","sequence":"first","affiliation":[{"name":"Data and Media Laboratory, Department of Electrical and Computer Engineering, University of Peloponnese, 22131 Tripoli, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-7063-130X","authenticated-orcid":false,"given":"Nikos","family":"Zotos","sequence":"additional","affiliation":[{"name":"Department of Management Science and Technology, University of Patras, 26334 Patras, Greece"}]},{"given":"Evangelos","family":"Mourelatos","sequence":"additional","affiliation":[{"name":"Department of Economics, Accounting and Finance, Oulu Business School, University of Oulu, FI-90014 Oulu, Finland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5989-6313","authenticated-orcid":false,"given":"Konstantinos C.","family":"Giotopoulos","sequence":"additional","affiliation":[{"name":"Department of Management Science and Technology, University of Patras, 26334 Patras, Greece"}]},{"given":"Panagiotis","family":"Zervas","sequence":"additional","affiliation":[{"name":"Data and Media Laboratory, Department of Electrical and Computer Engineering, University of Peloponnese, 22131 Tripoli, Greece"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"477","DOI":"10.1007\/s10844-017-0488-x","article-title":"WoLMIS: A labor market intelligence system for classifying web job vacancies","volume":"51","author":"Boselli","year":"2017","journal-title":"J. Intell. Inf. Syst."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Pavani, V., Pujitha, N., Vaishnavi, P., Neha, K., and Sahithi, D. (2022, January 16\u201318). Feature Extraction based Online Job Portal. Proceedings of the 2022 International Conference on Electronics and Renewable Systems (ICEARS), Tuticorin, India.","DOI":"10.1109\/ICEARS53579.2022.9752295"},{"key":"ref_3","unstructured":"Naveed, H., Khan, A., Qiu, S., Saqib, M., Anwar, S., Usman, M., Barnes, N., and Mian, A. (2023). A Comprehensive Overview of Large Language Models. arXiv."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"7913","DOI":"10.1038\/s41467-023-43713-1","article-title":"Augmenting interpretable models with large language models during training","volume":"14","author":"Singh","year":"2023","journal-title":"Nat. Commun."},{"key":"ref_5","unstructured":"(2024, May 01). CEDEFOP (European Centre for the Development of Vocational Training). Available online: https:\/\/www.cedefop.europa.eu\/en\/themes\/skills-labour-market."},{"key":"ref_6","unstructured":"Cedefop (2019). Online Job Vacancies and Skills Analysis: A Cedefop Pan-European Approach, Publications Office."},{"key":"ref_7","unstructured":"Cedefop (2019). The Online Job Vacancy Market in the EU: Driving Forces and Emerging Trends, Publications Office. Cedefop Research Paper; No 72."},{"key":"ref_8","unstructured":"(2024, May 01). Skills-OVATE Cedefop\u2019s Project. Available online: https:\/\/www.cedefop.europa.eu\/en\/tools\/skills-online-vacancies."},{"key":"ref_9","unstructured":"Carnevale, A.P., Jayasundera, T., and Repnikov, D. (2014). Understanding Online Job Ads Data, Georgetown Univ.. Center Educ. Workforce, Tech. Rep."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Brancatelli, C., Brodmann, S., and Marguerie, A. (2020). Job Creation and Demand for Skills in Kosovo: What Can We Learn from Job Portal Data?, The World Bank.","DOI":"10.1596\/1813-9450-9266"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1273","DOI":"10.1007\/s00181-023-02381-2","article-title":"Reacting Quickly and Protecting Jobs: The Short-Term Impacts of the COVID-19 Lockdown on the Greek Labor Market","volume":"65","author":"Betcherman","year":"2023","journal-title":"Empir. Econ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.is.2016.10.009","article-title":"Data Mining Approach to Monitoring The Requirements of the Job Market: A Case Study","volume":"65","author":"Karakatsanis","year":"2017","journal-title":"Inf. Syst."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Sibarani, E., Scerri, S., Morales, C., Auer, S., and Collarana, D. (2017, January 11\u201314). Ontology-guided Job Market Demand Analysis: A Cross-Sectional Study for the Data Science field. Proceedings of the 13th International Conference on Semantic Systems, Amsterdam, The Netherlands.","DOI":"10.1145\/3132218.3132228"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1016\/j.future.2018.03.035","article-title":"Classifying online Job Advertisements through Machine Learning","volume":"86","author":"Boselli","year":"2018","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Marrara, S., Pasi, G., Viviani, M., Cesarini, M., Mercorio, F., Mezzanzanica, M., and Pappagallo, M. (2017, January 23\u201326). A language modelling approach for discovering novel labor market occupations from the web. Proceedings of the 2017 IEEE\/WIC\/ACM International Conference on Web Intelligence (WI 2017), Leipzig, Germany.","DOI":"10.1145\/3106426.3109035"},{"key":"ref_16","unstructured":"(2024, May 01). ISCO-08 Classification (International Standard Classification of Occupations). Available online: https:\/\/ilostat.ilo.org\/methods\/concepts-and-definitions\/classification-occupation\/."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1016\/j.lisr.2016.11.006","article-title":"Research using job advertisements: A methodological assessment","volume":"38","author":"Kim","year":"2016","journal-title":"Libr. Inf. Sci. Res."},{"key":"ref_18","first-page":"111","article-title":"Text mining on job advertisement data: Systematic process for detecting artificial intelligence related jobs","volume":"Volume 2871","author":"Hajikhani","year":"2021","journal-title":"Proceedings of the 1st Workshop on AI + Informetrics (AII2021) Co-Located with the iConference 2021 (AII 2021)"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Bamieh, O., and Ziegler, L. (2020). How Does the COVID-19 Crisis Affect Labor Demand? An Analysis Using Job Board Data from Austria, IZA Institute of Labor Economics. IZA Discussion Paper No. 13801.","DOI":"10.2139\/ssrn.3718181"},{"key":"ref_20","unstructured":"(2024, May 01). ISCED (International Standard Classification of Education). Available online: https:\/\/ilostat.ilo.org\/resources\/concepts-and-definitions\/classification-education\/."},{"key":"ref_21","unstructured":"(2024, May 01). ICSE and ICSaW (International Classifications of Status in Employment and Status at Work). Available online: https:\/\/ilostat.ilo.org\/methods\/concepts-and-definitions\/classification-status-at-work\/."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Zhao, Y., Chen, H., and Mason, C.M. (2021, January 14\u201317). A framework for duplicate detection from online job postings. Proceedings of the 20th IEEE\/WIC\/ACM International Conference on Web Intelligence and Intelligent Agent Technology, Melbourne, Australia.","DOI":"10.1145\/3486622.3493928"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1287\/isre.2022.1104","article-title":"Handling Missing Values in Information Systems Research: A Review of Methods and Assumptions","volume":"34","author":"Peng","year":"2023","journal-title":"Inf. Syst. Res."},{"key":"ref_24","unstructured":"(2024, May 01). ESCO (European Skills, Competences, Qualifications and Occupations). Available online: https:\/\/esco.ec.europa.eu\/en\/classification\/occupation_main."},{"key":"ref_25","unstructured":"(2024, May 01). ISIC (International Standard Industrial Classification of All Economic Activities). Available online: https:\/\/unstats.un.org\/unsd\/publication\/seriesm\/seriesm_4rev4e.pdf."},{"key":"ref_26","unstructured":"(2024, May 01). NAICS (North American Industry Classification System). Available online: https:\/\/www.naics.com\/."},{"key":"ref_27","unstructured":"(2024, May 01). NACE Rev.2 (Statistical classification of economic activities in the European Community). Available online: https:\/\/ec.europa.eu\/eurostat\/documents\/3859598\/5902521\/KS-RA-07-015-EN.PDF."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"807","DOI":"10.3233\/SJI-200675","article-title":"Exploring a knowledge-based approach to predicting NACE codes of enterprises based on web page texts","volume":"36","author":"Windmeijer","year":"2020","journal-title":"Stat. J. IAOS"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Roy, S., Chiticariu, L., Feldman, V., Reiss, F., and Zhu, H. (2013, January 22\u201327). Provenance-based dictionary refinement in information extraction. Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data (SIGMOD\u201913), New York, NY, USA.","DOI":"10.1145\/2463676.2465284"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"294","DOI":"10.1016\/j.physa.2004.01.072","article-title":"Dictionary based methods for information extraction","volume":"342","author":"Baronchelli","year":"2004","journal-title":"Phys. A Stat. Mech. Its Appl."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1257\/jep.35.3.3","article-title":"Effects of the COVID-19 recession on the US labor market: Occupation, family, and gender","volume":"35","author":"Albanesi","year":"2021","journal-title":"J. Econ. Perspect."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"157595","DOI":"10.1109\/ACCESS.2019.2949905","article-title":"Extracting Knowledge from On-Line Sources for Software Engineering Labor Market: A Mapping Study","volume":"7","author":"Papoutsoglou","year":"2019","journal-title":"IEEE Access"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1013","DOI":"10.1093\/jssam\/smaa023","article-title":"Machine learning for occupation coding\u2014A comparison study","volume":"9","author":"Schierholz","year":"2020","journal-title":"J. Surv. Stat. Methodol."},{"key":"ref_34","unstructured":"Djumalieva, J., Lima, A., and Sleeman, C. (2018). Classifying Occupations According to Their Skill Requirements in Job Advertisements, Economic Statistics Centre of Excellence. Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-04, Economic Statistics Centre of Excellence (ESCoE)."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1883698","DOI":"10.1155\/2022\/1883698","article-title":"A Complete Process of Text Classification System Using State-of-the-Art NLP Models","volume":"2022","author":"Dogra","year":"2022","journal-title":"Comput. Intell. Neurosci."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Zhang, M., Jensen, K., Sonniks, S., and Plank, B. (2022, January 10\u201315). SkillSpan: Hard and Soft Skill Extraction from English Job Postings. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Seattle, WA, USA.","DOI":"10.18653\/v1\/2022.naacl-main.366"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"115544","DOI":"10.1016\/j.eswa.2021.115544","article-title":"SkillNER: Mining and mapping soft skills from any text","volume":"184","author":"Fareri","year":"2021","journal-title":"Expert Syst. Appl."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Djumalieva, J., and Sleeman, C. (2018). An Open and Data-Driven Taxonomy of Skills Extracted from Online Job Adverts, Economic Statistics Centre of Excellence. Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-13, Economic Statistics Centre of Excellence (ESCoE).","DOI":"10.5771\/9783957103154-425"},{"key":"ref_39","unstructured":"NESTA (2024, May 01). The Open Jobs Observatory. Available online: https:\/\/www.nesta.org.uk\/project\/open-jobs-observatory\/."},{"key":"ref_40","unstructured":"Demunter, C., and Dimitrakopoulou, K. (2013). One in Seven Businesses Belong to the Tourism Industries, EDC collection. Industry, Trade and Services, European Union. Volumes 32-2013 of Statistics in Focus."}],"container-title":["Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2078-2489\/15\/8\/496\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T15:39:18Z","timestamp":1760110758000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2078-2489\/15\/8\/496"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,20]]},"references-count":40,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2024,8]]}},"alternative-id":["info15080496"],"URL":"https:\/\/doi.org\/10.3390\/info15080496","relation":{},"ISSN":["2078-2489"],"issn-type":[{"value":"2078-2489","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8,20]]}}}