Text Mining in Scientific Literature Evaluation: Extraction of Keywords for Describing Content
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3AMHWQ6ZZU" target="_blank" >RIV/00216208:11320/23:MHWQ6ZZU - isvavai.cz</a>
Result on the web
<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85160501428&doi=10.1007%2f978-3-658-38798-3_11&partnerID=40&md5=105ae035787b7d988e0274626e3b98e1" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85160501428&doi=10.1007%2f978-3-658-38798-3_11&partnerID=40&md5=105ae035787b7d988e0274626e3b98e1</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-658-38798-3_11" target="_blank" >10.1007/978-3-658-38798-3_11</a>
Alternative languages
Result language
angličtina
Original language name
Text Mining in Scientific Literature Evaluation: Extraction of Keywords for Describing Content
Original language description
"Keywords should represent the content of documents in a compact form. They serve to assign suitable publications to a search query in the context of a scientific literature search. If a literature search is carried out as part of a scientific work, the found publications must be analyzed and their content evaluated. This can be a large number of publications, so that the analysis of the content can be extremely time-consuming. This article describes how the analysis of publications can be supported by text mining in the context of “Explainable AI” literature evaluation. Keywords are extracted from the abstracts of the found publications by text mining. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2023."
Czech name
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Czech description
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Classification
Type
C - Chapter in a specialist book
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Book/collection name
"Apply Data Science: Introduction, Applications and Projects"
ISBN
978-365838798-3
Number of pages of the result
7
Pages from-to
181-187
Number of pages of the book
439
Publisher name
Springer Fachmedien Wiesbaden
Place of publication
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UT code for WoS chapter
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