{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T16:45:57Z","timestamp":1780418757565,"version":"3.54.1"},"reference-count":36,"publisher":"Oxford University Press (OUP)","issue":"Supplement_1","license":[{"start":{"date-parts":[[2023,6,1]],"date-time":"2023-06-01T00:00:00Z","timestamp":1685577600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"name":"Department of Linguistic and Literary Studies"},{"DOI":"10.13039\/501100003500","name":"University of Padua","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003500","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,6,21]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Automatic Term Extraction (ATE) systems have been studied for many decades as, among other things, one of the most important tools for tasks such as information retrieval, sentiment analysis, named entity recognition, and others. The interest in this topic has even increased in recent years given the support and improvement of the new neural approaches. In this article, we present a follow-up on the discussions about the pipeline that allows extracting key terms from medical reports, presented at MDTT 2022, and analyze the very last papers about ATE in a systematic review fashion. We analyzed the journal and conference papers published in 2022 (and partially in 2023) about ATE and cluster them into subtopics according to the focus of the papers for a better presentation.<\/jats:p>","DOI":"10.1093\/llc\/fqad030","type":"journal-article","created":{"date-parts":[[2023,6,21]],"date-time":"2023-06-21T09:13:27Z","timestamp":1687338807000},"page":"i41-i47","source":"Crossref","is-referenced-by-count":7,"title":["A systematic review of Automatic Term Extraction: What happened in 2022?"],"prefix":"10.1093","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9709-6392","authenticated-orcid":false,"given":"Giorgio Maria","family":"Di Nunzio","sequence":"first","affiliation":[{"name":"Department of Information Engineering, University of Padova , Via Gradenigo 6a , Padova 35131, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0362-5893","authenticated-orcid":false,"given":"Stefano","family":"Marchesin","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, University of Padova , Via Gradenigo 6a , Padova 35131, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4970-4554","authenticated-orcid":false,"given":"Gianmaria","family":"Silvello","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, University of Padova , Via Gradenigo 6a , Padova 35131, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2023,6,21]]},"reference":[{"issue":"1","key":"2023062109132163700_fqad030-B1","first-page":"1","article-title":"Utilising heterogeneous language resources for term extraction in maritime 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