Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Chapter
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Chapter
}
TY - CHAP
T1 - A mobile cloud framework for context-aware and portable recommender system for smart markets
AU - Khan, Aftab
AU - Ahmad, Aakash
AU - Rahman, Anis Ur
AU - Alkhalil, Adel
N1 - Publisher Copyright: © 2020, Springer Nature Switzerland AG.
PY - 2019/6/21
Y1 - 2019/6/21
N2 - Smart city systems are fast emerging as solutions that provide better and digitized urban services to empower individuals and organizations. Mobile and cloud computing technologies can enable smart city systems to (1) exploit the portability and context-awareness of mobile devices and (2) utilize the computation and storage services of cloud servers. Despite the wide-spread adoption of mobile and cloud computing technologies, there is still a lack of solutions that provide the users with portable and context-aware recommendations based on their localized context. We propose to advance the state-of-the-art on recommender systems—providing a portable, efficient, and context-driven digital matchmaking—in the context of smart markets that involves virtualized customers and business entities. We have proposed a framework and algorithms that unify the mobile and cloud computing technologies to offer context-aware and portable recommendations for smart markets. We have developed a prototype as a proof-of-the-concept to support automation, user intervention, and customization of users’ preferences during the recommendation process. The evaluation results suggest that the framework (1) has a high accuracy for context-aware recommendations, and (2) it supports computation and energy efficient mobile computing. The proposed solution aims to advance the research on recommender systems for smart city systems by providing context-aware and portable computing for smart markets.
AB - Smart city systems are fast emerging as solutions that provide better and digitized urban services to empower individuals and organizations. Mobile and cloud computing technologies can enable smart city systems to (1) exploit the portability and context-awareness of mobile devices and (2) utilize the computation and storage services of cloud servers. Despite the wide-spread adoption of mobile and cloud computing technologies, there is still a lack of solutions that provide the users with portable and context-aware recommendations based on their localized context. We propose to advance the state-of-the-art on recommender systems—providing a portable, efficient, and context-driven digital matchmaking—in the context of smart markets that involves virtualized customers and business entities. We have proposed a framework and algorithms that unify the mobile and cloud computing technologies to offer context-aware and portable recommendations for smart markets. We have developed a prototype as a proof-of-the-concept to support automation, user intervention, and customization of users’ preferences during the recommendation process. The evaluation results suggest that the framework (1) has a high accuracy for context-aware recommendations, and (2) it supports computation and energy efficient mobile computing. The proposed solution aims to advance the research on recommender systems for smart city systems by providing context-aware and portable computing for smart markets.
KW - Mobile cloud computing
KW - Mobile computing
KW - Recommendation system
KW - Smart city software
KW - Smart markets
KW - Software engineering
UR - http://www.scopus.com/inward/record.url?scp=85089464334&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-13705-2_12
DO - 10.1007/978-3-030-13705-2_12
M3 - Chapter
AN - SCOPUS:85089464334
SN - 978-3-030-13704-5
T3 - EAI/Springer Innovations in Communication and Computing
SP - 283
EP - 309
BT - EAI/Springer Innovations in Communication and Computing
A2 - Mehmood, Rashid
A2 - See, Simon
A2 - Katib, Iyad
A2 - Chlamtac, Imrich
PB - Springer Science and Business Media Deutschland GmbH
ER -