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AuthorRafique, Wajid
AuthorHafid, Abdelhakim Senhaji
AuthorQadir, Junaid
Available date2023-07-13T05:40:52Z
Publication Date2023
Publication NameTransactions on Emerging Telecommunications Technologies
ResourceScopus
ISSN21613915
URIhttp://dx.doi.org/10.1002/ett.4728
URIhttp://hdl.handle.net/10576/45584
AbstractSmart cities could be defined as urban areas that use Information and Communication Technology (ICT) to solve city problems in efficient and sustainable ways. Intent-aware Recommender Systems (IARS) within ICT play a crucial role in filtering useless information according to user demands and assist in decision-making in various smart city platforms. In smart cities, the user traces on IoT, RFIDs, mobiles, and smart sensors capture actual user intent of performing an activity and enhance user satisfaction by proposing optimal services. This paper presents a detailed literature survey of the field of IARS and how it can be used for developing smart city services. First, we present the evolution of IARS with the development of computing technology. Then, we present case studies, synergies, advances, and a reference implementation architecture of IARS for smart cities. We discuss requirements for developing smart city services using IARS. Furthermore, we devise a comprehensive taxonomy of applications and techniques of IARS using different performance parameters. Finally, we elaborate on current issues, challenges, and future research directions in IARS; these directions we believe will pave the way for autonomous service provisioning in smart cities. 2023 John Wiley & Sons, Ltd.
SponsorQatar National Research Fund, Grant/Award Number: 13S-0206-200273 Funding information
Languageen
PublisherJohn Wiley and Sons Inc
SubjectDecision making
Information filtering
Smart city
Case-studies
Computing technology
Decisions makings
Information and Communication Technologies
Literature survey
Reference implementation
Urban areas
User demands
User trace
Users' satisfactions
Recommender systems
TitleDeveloping smart city services using intent-aware recommendation systems: A survey
TypeArticle
Issue Number4
Volume Number34


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