Leveraging Natural Language Processing to Analyze Scientific Content: Proposal of an NLP Pipeline for the Field of Computer Vision
Autor(en): | Kortum, H. Leimkühler, M. Thomas, O. |
Herausgeber: | Ahlemann, F. Schutte, R. Stieglitz, S. |
Stichwörter: | Computer vision; Emerging trends; Machine learning; Natural language processing; W2V | Erscheinungsdatum: | 2021 | Herausgeber: | Springer Science and Business Media Deutschland GmbH | Journal: | Lecture Notes in Information Systems and Organisation | Volumen: | 47 | Startseite: | 40 | Seitenende: | 55 | Zusammenfassung: | In this paper we elaborate the opportunity of using natural language processing to analyze scientific content both, from a practical as well as a theoretical point of view. Firstly, we conducted a literature review to summarize the status quo of using natural language processing for analyzing scientific content. We could identify different approaches, e.g., with the aim of clustering and tagging publications or to summarize scientific papers. Secondly, we conducted a case study where we used our proposed natural language processing pipeline to analyze scientific content about computer vision available at the database IEEE. Our method helped us to identify emerging trends in the recent years and give an overview of the field of research. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG. |
Beschreibung: | Conference of 16th International Conference on Business Information Systems Engineering, WI 2021 ; Conference Date: 9 March 2021 Through 11 March 2021; Conference Code:267099 |
ISBN: | 9783030867966 | ISSN: | 21954968 | DOI: | 10.1007/978-3-030-86797-3_3 | Externe URL: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118181340&doi=10.1007%2f978-3-030-86797-3_3&partnerID=40&md5=865fa52d80498c2c752859b438f32c59 |
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geprüft am 21.05.2024