{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T02:39:48Z","timestamp":1778121588705,"version":"3.51.4"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,8]]},"abstract":"<jats:p>In this paper, we present Skills2Graph, a tool that, starting from a set of users\u2019 professional skills, identifies the most suitable jobs as they emerge from a large corpus of 2.5M+ Online Job Vacancies (OJVs) posted in three different countries (the United Kingdom, France, and Germany). To this aim, we rely both on co-occurrence statistics - computing a count-based measure of skill-relevance named Revealed Comparative Advantage (rca) - and distributional semantics - generating several embeddings on the OJVs corpus and performing an intrinsic evaluation of their quality. Results, evaluated through a user study of 10 labor market experts, show a high P@3 for the recommendations provided by Skills2Graph, and a high nDCG (0.985 and 0.984 in a [0,1] range), that indicates a strong correlation between the experts\u2019 scores and the rankings generated by Skills2Graph.<\/jats:p>","DOI":"10.24963\/ijcai.2021\/708","type":"proceedings-article","created":{"date-parts":[[2021,8,11]],"date-time":"2021-08-11T11:00:49Z","timestamp":1628679649000},"page":"4984-4987","source":"Crossref","is-referenced-by-count":5,"title":["Skills2Graph: Processing million Job Ads to face the Job Skill Mismatch Problem"],"prefix":"10.24963","author":[{"given":"Anna","family":"Giabelli","sequence":"first","affiliation":[{"name":"Dept. of Informatics, Systems and Communication, University of Milano Bicocca, Milan, Italy"}]},{"given":"Lorenzo","family":"Malandri","sequence":"additional","affiliation":[{"name":"Dept. of Statistics and Quantitative Methods, University of Milano Bicocca, Milan, Italy"}]},{"given":"Fabio","family":"Mercorio","sequence":"additional","affiliation":[{"name":"Dept. of Statistics and Quantitative Methods, University of Milano Bicocca, Milan, Italy"}]},{"given":"Mario","family":"Mezzanzanica","sequence":"additional","affiliation":[{"name":"Dept. of Statistics and Quantitative Methods, University of Milano Bicocca, Milan, Italy"}]},{"given":"Andrea","family":"Seveso","sequence":"additional","affiliation":[{"name":"Dept. of Informatics, Systems and Communication, University of Milano Bicocca, Milan, Italy"}]}],"member":"10584","event":{"name":"Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}","theme":"Artificial Intelligence","location":"Montreal, Canada","acronym":"IJCAI-2021","number":"30","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2021,8,19]]},"end":{"date-parts":[[2021,8,27]]}},"container-title":["Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2021,8,11]],"date-time":"2021-08-11T11:04:48Z","timestamp":1628679888000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2021\/708"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2021,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2021\/708","relation":{},"subject":[],"published":{"date-parts":[[2021,8]]}}}