Analysing Trust, Security and Cost of Cloud Consumer’s Reviews using RNN, LSTM, and GRU

Raza, MR; Hussain, W; Rajaeian, M

Analysing Trust, Security and Cost of Cloud Consumer’s Reviews using RNN, LSTM, and GRU

Raza, MR Hussain, W

Rajaeian, M

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Publisher:: Taylor & Francis
Publication Type:: Chapter
Citation:: Advances in Complex Decision Making: Using Machine Learning and Tools for Service-Oriented Computing, 2024, pp. 52-65
Issue Date:: 2024

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Field	Value	Language
dc.contributor.author	Raza, MR
dc.contributor.author	Hussain, W https://orcid.org/0000-0003-0610-4006
dc.contributor.author	Rajaeian, M
dc.date.accessioned	2024-08-22T02:43:30Z
dc.date.available	2024-08-22T02:43:30Z
dc.date.issued	2024
dc.identifier.citation	Advances in Complex Decision Making: Using Machine Learning and Tools for Service-Oriented Computing, 2024, pp. 52-65
dc.identifier.isbn	9781032375274
dc.identifier.uri	http://hdl.handle.net/10453/180533
dc.description.abstract	People frequently seek out the advice of others and ask for recommendations before making decisions. They share their suggestions online, thanks to public social media. Customers often search for a product before purchasing it, and online reviews have a major impact on their decision. Companies may learn more about people’s thoughts and preferences by soliciting feedback on their goods through formal and informal communication channels [1]. In many cases, assessing sentiments independently for each business factor is more valuable than obtaining the general sentiment of a topic.
dc.language	en
dc.publisher	Taylor & Francis
dc.relation.ispartof	Advances in Complex Decision Making: Using Machine Learning and Tools for Service-Oriented Computing
dc.relation.isbasedon	10.1201/9781003340621-4
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Analysing Trust, Security and Cost of Cloud Consumer’s Reviews using RNN, LSTM, and GRU
dc.type	Chapter
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2024-08-22T02:43:27Z
pubs.publication-status	Published

Abstract:

People frequently seek out the advice of others and ask for recommendations before making decisions. They share their suggestions online, thanks to public social media. Customers often search for a product before purchasing it, and online reviews have a major impact on their decision. Companies may learn more about people’s thoughts and preferences by soliciting feedback on their goods through formal and informal communication channels [1]. In many cases, assessing sentiments independently for each business factor is more valuable than obtaining the general sentiment of a topic.

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http://hdl.handle.net/10453/180533