Keyword extraction from news corpus by deep learning in the context of internet of things. (15th May 2023)
- Record Type:
- Journal Article
- Title:
- Keyword extraction from news corpus by deep learning in the context of internet of things. (15th May 2023)
- Main Title:
- Keyword extraction from news corpus by deep learning in the context of internet of things
- Authors:
- Xiao, Yan
- 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.
- Is Part Of:
- International journal of grid and utility computing. Volume 14:Number 2/3(2023)
- Journal:
- International journal of grid and utility computing
- Issue:
- Volume 14:Number 2/3(2023)
- Issue Display:
- Volume 14, Issue 2/3 (2023)
- Year:
- 2023
- Volume:
- 14
- Issue:
- 2/3
- Issue Sort Value:
- 2023-0014-NaN-0000
- Page Start:
- 75
- Page End:
- 93
- Publication Date:
- 2023-05-15
- Subjects:
- internet of things -- optical character recognition technology -- news corpus -- deep learning -- Bi-LSTM-CRF
Electronic data processing -- Distributed processing -- Periodicals
Electronic commerce -- Management -- Computer programs -- Periodicals
004.605 - Journal URLs:
- http://www.inderscience.com/ ↗
http://www.inderscience.com/jhome.php?jcode=ijguc ↗ - Languages:
- English
- ISSNs:
- 1741-847X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 26683.xml