@article {Khaouja2021118134,
	title = {A Survey on Skill Identification from Online Job Ads},
	journal = {IEEE Access},
	volume = {9},
	year = {2021},
	note = {cited By 8},
	pages = {118134-118153},
	abstract = {A changing job market, influenced by different factors such as globalization and demographic growth, urges close monitoring. The digitization of the job market has given the opportunity to researchers to better understand job market needs as job postings/ads become more accessible. However, such postings are submitted in unstructured text and need further processing to identify the required skills. The aim of this survey is to review current research on skill identification from job ads and to discuss possible future research directions. In this study, we systematically reviewed 108 research articles on the topic. In particular, we evaluated and classified the prior work aiming to identify the skill bases used for analyzing job market needs; the type of extracted skills; the skill identification methods; the studied sector and the skill identification granularity. Then, we categorized the existent applications and goals of skill identification. Finally, we present key challenges and discuss recent trends. {\textcopyright} 2013 IEEE.},
	keywords = {Commerce, Demographic growth, Employment, Identification method, Job market, Job postings, Possible futures, Recent trends, Surveys, Unstructured texts},
	doi = {10.1109/ACCESS.2021.3106120},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113305279\&doi=10.1109\%2fACCESS.2021.3106120\&partnerID=40\&md5=95e3da9f3201c5b0ca744ba8d8af7012},
	author = {Khaouja, I. and Kassou, I. and Ghogho, M.}
}
