Periodical Mobile Recommendation Toward Parking Conflict Reduction

Srisura, Benjawan; Avatchanakorn, Vichit

doi:10.1109/iea.2019.8715025

Cited by 5 publications

(4 citation statements)

References 2 publications

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“…Therefore, accurate recommendations resulted in parking issues. To address this problem, the work in [59] proposed a periodical recommendation that is conducted during three periods: recommendations at the entry gate, recommendations for the nearest parking zone, and recommendations for the new zone, when the recommended parking is taken. The system uses three main dimensions as data sources: user profile, user preferences, and nearest zone.…”

Section: Content-based Approachmentioning

confidence: 99%

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A Survey on Recommender Systems for Internet of Things: Techniques, Applications and Future Directions

Altulyan

Yao

Wang

et al. 2021

The Computer Journal

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Recommendation is a critical tool for developing and promoting the benefits of the Internet of Things (IoT). In recent years, recommender systems have attracted considerable attention in many IoT-related fields such as smart health, smart home, smart tourism and smart marketing. However, traditional recommender system approaches fail to exploit ever-growing, dynamic and heterogeneous IoT data in building recommender systems for the IoT (RSIoT). This article aims to provide a comprehensive review of state-of-the-art RSIoT, including the related techniques, applications and a discussion on the limitations of applying recommendation systems to IoT. Finally, we propose a reference framework for comparing existing studies to guide future research and practices.

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Section: Content-based Approachmentioning

confidence: 99%

“…To address these problems, in [59], an application for parking conflict reduction was proposed that uses a periodical recommendation. Parking spaces that are available at different periods during the day are recommended to ensure accuracy.…”

Section: Smart Car-parkingmentioning

confidence: 99%

A Survey on Recommender Systems for Internet of Things: Techniques, Applications and Future Directions

Altulyan

Yao

Wang

et al. 2021

The Computer Journal

View full text Add to dashboard Cite

show abstract

“…Therefore, accurate recommendations resulted in parking issues. To address this problem, the work in [104] proposed a periodical recommendation that is conducted during three periods: recommendations at the entry gate, recommendations for the nearest parking zone and recommendations for the new zone, when the recommended parking is taken. The system uses three main dimensions as data sources: user profile, user preferences and nearest zone.…”

Section: Content-based Approachmentioning

confidence: 99%

“…These two problems cause conflict parking. To address these problems, in [104], an application for parking conflict reduction was proposed that uses a periodical recommendation. Parking spaces that are available at different periods during the day are recommended to ensure the accuracy.…”

Section: Smart Car-parkingmentioning

confidence: 99%

Recommender Systems for the Internet of Things: A Survey

Altulyan,

Yao,

Wang

et al. 2020

Preprint

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Recommendation represents a vital stage in developing and promoting the benefits of the Internet of Things (IoT). Traditional recommender systems fail to exploit ever-growing, dynamic, and heterogeneous IoT data. This paper presents a comprehensive review of the state-of-the-art recommender systems, as well as related techniques and application in the vibrant field of IoT. We discuss several limitations of applying recommendation systems to IoT and propose a reference framework for comparing existing studies to guide future research and practices.

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