A spark‐based big data analysis framework for real‐time sentiment prediction on streaming data
- Authors:
-
- Department of Software Engineering, Faculty of TechnologyManisa Celal Bayar University Manisa Turkey
- Publication Date:
- Sponsoring Org.:
- USDOE Office of Electricity (OE), Advanced Grid Research & Development. Power Systems Engineering Research
- OSTI Identifier:
- 1529994
- Resource Type:
- Publisher's Accepted Manuscript
- Journal Name:
- Software, Practice and Experience
- Additional Journal Information:
- Journal Name: Software, Practice and Experience Journal Volume: 49 Journal Issue: 9; Journal ID: ISSN 0038-0644
- Publisher:
- Wiley Blackwell (John Wiley & Sons)
- Country of Publication:
- United Kingdom
- Language:
- English
Citation Formats
Kılınç, Deniz. A spark‐based big data analysis framework for real‐time sentiment prediction on streaming data. United Kingdom: N. p., 2019.
Web. doi:10.1002/spe.2724.
Kılınç, Deniz. A spark‐based big data analysis framework for real‐time sentiment prediction on streaming data. United Kingdom. doi:10.1002/spe.2724.
Kılınç, Deniz. Thu .
"A spark‐based big data analysis framework for real‐time sentiment prediction on streaming data". United Kingdom. doi:10.1002/spe.2724.
@article{osti_1529994,
title = {A spark‐based big data analysis framework for real‐time sentiment prediction on streaming data},
author = {Kılınç, Deniz},
abstractNote = {},
doi = {10.1002/spe.2724},
journal = {Software, Practice and Experience},
number = 9,
volume = 49,
place = {United Kingdom},
year = {2019},
month = {6}
}
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DOI: 10.1002/spe.2724
DOI: 10.1002/spe.2724
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