Title: Keyword extraction from news corpus by deep learning in the context of internet of things

Authors: Yan Xiao

Addresses: School of Humanities, Hunan City University, Yiyang 413000, Hunan, China

Abstract: With the rapid development of modern technology and information technology, information generation and dissemination is getting faster and faster. The amount of web text, such as web pages, e-books, news, etc., is exploding. Therefore, it is very important for users to quickly and accurately find out what they are interested in from the large amount of data in the network. Keywords can help users quickly understand the main content of the text and the main idea, improve query efficiency, and save search time. Therefore, in order to solve the problem of increasing information volume, searching for the information people need more efficiently, exploring new technologies for keyword extraction, and improving the accuracy of keyword extraction are more and more important.

Keywords: internet of things; optical character recognition technology; news corpus; deep learning; Bi-LSTM-CRF.

DOI: 10.1504/IJGUC.2023.131005

International Journal of Grid and Utility Computing, 2023 Vol.14 No.2/3, pp.75 - 93

Received: 03 May 2022
Received in revised form: 07 Aug 2022
Accepted: 14 Aug 2022
Published online: 18 May 2023 *

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