Automatic genre identification: a survey: Automatic genre identification: a survey: T. Kuzman, N. Ljubešić.
Automatic genre identification (AGI) is a text classification task focused on genres, i.e., text categories defined by the author's purpose, common function of the text, and the text's conventional form. Obtaining genre information has been shown to be beneficial for a wide range of disciplines, inc...
| Publicado en: | Language Resources & Evaluation Vol. 59; no. 1; pp. 537 - 571 |
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| Autores principales: | , |
| Formato: | Literature Review |
| Publicado: |
Springer Nature
Mar2025
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=183750656&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 183750656 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 1574020X 179V jtl: Language Resources & Evaluation issn: 1574020X maglogo: N pubinfo: dt: Mar2025 vid: 59 iid: 1 pid: 237 pub: Springer Nature artinfo: ui: 183750656 10.1007/s10579-023-09695-8 ppf: 537 ppct: 34 formats: fmt: – @attributes: type: T – @attributes: type: P size: 1.7MB tig: atl: Automatic genre identification: a survey: Automatic genre identification: a survey: T. Kuzman, N. Ljubešić. aug: au: Kuzman, Taja Ljubešić, Nikola affil: https://ror.org/01hdkb925 Department of Knowledge Technologies, Jožef Stefan Institute, Jamova cesta 39, 1000, Ljubljana, Slovenia https://ror.org/01hdkb925 Jožef Stefan International Postgraduate School, Jamova cesta 39, 1000, Ljubljana, Slovenia https://ror.org/05njb9z20 Faculty of Computer and Information Science, University of Ljubljana, Večna pot 113, 1000, Ljubljana, Slovenia su: Natural language processing Automatic identification Information technology security Computational linguistics Corpora sug: subj: Natural language processing Automatic identification Information technology security Computational linguistics Corpora keyword: Automatic genre identification Communication and Culture Linguistics Genre datasets Genre schemata Information and Computing Sciences Artificial Intelligence and Image Processing Language Survey paper Text genre Web genre ab: Automatic genre identification (AGI) is a text classification task focused on genres, i.e., text categories defined by the author's purpose, common function of the text, and the text's conventional form. Obtaining genre information has been shown to be beneficial for a wide range of disciplines, including linguistics, corpus linguistics, computational linguistics, natural language processing, information retrieval and information security. Consequently, in the past 20 years, numerous researchers have collected genre datasets with the aim to develop an efficient genre classifier. However, their approaches to the definition of genre schemata, data collection and manual annotation vary substantially, resulting in significantly different datasets. As most AGI experiments are dataset-dependent, a sufficient understanding of the differences between the available genre datasets is of great importance for the researchers venturing into this area. In this paper, we present a detailed overview of different approaches to each of the steps of the AGI task, from the definition of the genre concept and the genre schema, to the dataset collection and annotation methods, and, finally, to machine learning strategies. Special focus is dedicated to the description of the most relevant genre schemata and datasets, and details on the availability of all of the datasets are provided. In addition, the paper presents the recent advances in machine learning approaches to automatic genre identification, and concludes with proposing the directions towards developing a stable multilingual genre classifier. pubtype: Academic Journal doctype: Literature Review src: R language: English refInfo: copyright: @attributes: flag: Y custom: Language Resources & Evaluation is a copyright of Springer, 2025. All Rights Reserved. item: Language Resources & Evaluation holder: Springer Nature dt: @attributes: year: 2025 holdings: @attributes: islocal: N |
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