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Title: A spark‐based big data analysis framework for real‐time sentiment prediction on streaming data

Authors:
ORCiD logo [1]
  1. 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}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.1002/spe.2724

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