Affiliation:
1. Department of Information Engineering, University of Padova , Via Gradenigo 6a , Padova 35131, Italy
Abstract
Abstract
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.
Funder
Department of Linguistic and Literary Studies
University of Padua
Publisher
Oxford University Press (OUP)
Subject
Computer Science Applications,Linguistics and Language,Language and Linguistics,Information Systems
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献