Volume 5, Issue 2, June 2020, Page: 82-92
Cyber Physical Recommender Systems for IoT Based Applications
Anagha Neelkanth Chaudhari, Department of Computer Engineering, Pimpri Chinchwad College of Engineering, SPPU, Pune, India
Received: Apr. 10, 2020;       Accepted: Apr. 23, 2020;       Published: May 19, 2020
DOI: 10.11648/j.ajset.20200502.14      View  282      Downloads  117
Cyber-physical systems (CPS) are often characterized as smart systems, which intelligently interact with other systems across information and physical interfaces. Cyber-physical systems (CPS) are fitting into modern society. CPS integrate multiple techniques, including distributed computing, communication and automatic control, to support variety of intelligent services and applications in many fields, such as transportation, healthcare, entertainment and city infrastructure. Recommender systems in CPS, which always provide information recommendations for users based on historical ratings collected from a single domain only, suffer from the data sparsity problem. Recently, several recommendation models have been proposed to transfer knowledge across multiple domains to alleviate the sparsity problem, which typically assumes that multiple domains share a latent common rating pattern. Recommender systems always results into faster and efficient options/choices as per user’s demands. This technology helps us in retrieval and access of different services like in Healthcare sector, Education, E-Commerce, etc. During the last few decades, with the rise of Youtube, Amazon, Netflix and many other such web services, recommender systems have taken more and more place in our lives. From e-commerce (suggest to buyers articles that could interest them) to online advertisement (suggest to users the right contents, matching their preferences), recommender systems are today unavoidable in our daily online journeys. In this paper, a proposed system architecture focusses on IoT applications utilizing recommender systems for offering number of services to users. Also, various Cyber Physical Recommender Systems are proposed to offer standard quality of service (QoS) for various IoT applications.
Cyber Physical Systems (CPS), Internet of Things, Recommender Systems (RS), Collaborative Filtering, Content Based and Hybrid Recommendation
To cite this article
Anagha Neelkanth Chaudhari, Cyber Physical Recommender Systems for IoT Based Applications, American Journal of Science, Engineering and Technology. Special Issue: Recommender Systems Using Cyber Physical Techniques. Vol. 5, No. 2, 2020, pp. 82-92. doi: 10.11648/j.ajset.20200502.14
Copyright © 2020 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Jiachen Xu, Anfeng Liu, NaixueXiong, TianWang and Zhengbang Zuo, “Integrated collaborative filtering recommendation in social cyber-physical systems”, International Journal of Distributed Sensor Networks 2017, Vol. 13 (12). The Author (s) 2017, DOI: 10.1177/1550147717749745, journals.sagepub.com/home/ds.
Sheng Gao, Hao Luo, Da Chen, Shantao Li, Patrick Gallinari, Zhanyu Ma, Jun Guo, “A Cross-Domain Recommendation Model for Cyber-Physical Systems”, School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China, Dec. 2013, pp. 384-393, vol. 1, DOI Bookmark: 10.1109/TETC.2013.2274044.
Runhe Huang, Laurence Tianruo Yang, “Cybermatics: A Holistic Field for Systematic Study of Cyber-Enabled New Worlds”, Special Section On Big Data Services And Computational Intelligence For Industrial Systems, Tokyo, Japan, IEEE Access.
Jayashree Salunke and Anagha Chaudhari, “Classification of Recommendation System for E-commerce Application” in the Journal of Computer Science Engineering and Software Testing (MAT Journals) November 2017.
Ms. Anagha Chaudhari, Dr. Swati Shinde, “Effective And Fast Retrieval Of Medical Records From Recommender Based Systems, International Journal of Engineering Applied Sciences and Technology, 2016, Vol. 1, No. 8, Pages 1-6, Published Online June – July 2016 in IJEAST (http://www.ijeast.com).
Ibrahim Mashal, Tein yaw David Chung, ama Alsaryrah, “Toward Service Recommendation in Internet of Things”, Yuan Ze University, Taoyuan, Taiwan, Conference Paper • July 2015, DOI: 10.1109/ICUFN.2015.7182559.
Akshita, Smita, “Recommender System: Review”, PDM College Of Engineering, Haryana, India, International Journal of Computer Applications (0975 – 8887), Volume 71 – No. 24, June 2013.
Rachad Atat, Lingjia Liu, Senior Member, IEEE, Jinsong Wu, Senior Member, IEEE, Guangyu Li, Chunxuan Ye, and Yang Yi, Senior Member, IEEE, “Big Data Meet Cyber-Physical Systems: A Panoramic Survey”, arXiv: 1810.12399v1 [cs. LG] 29 Oct 2018.
Alexander Felfernig, Seda Polat Erdeniz, Michael Jerana, Arda Akcaya, Paolo Azzonib, Matteo Maierob, Charalampos Doukas, “Recommendation Technologies for IoT Edge Devices “, The 3rd International Workshop on Internet of Things: Networking, Applications and Technologies (IoTNAT 2017), Italy, © 2017 The Authors. Published by Elsevier B. V.
Chi Harold Liu, Member, IEEE, Zhen Zhang, and Min Chen, Senior Member, IEEE, “Personalized Multimedia Recommendations for Cloud-Integrated Cyber-Physical Systems”, IEEE SYSTEMS JOURNAL 2015.
Yuyu Yin, Fangzheng Yu, Yueshen Xu, Lifeng Yu and Jinglong Mu, “Network Location-Aware Service Recommendation with Random Walk in Cyber-Physical Systems”.
Sergio Di Martino, Silvia Rossi, “An Architecture for a Mobility Recommender System in Smart Cities”, International Workshop on Data Mining on IoT Systems (DaMIS16), _ 2016 The Authors. Published by Elsevier B. V.
Remo Manuel Frey, Runhua Xu, and Alexander Ilic, “A Novel Recommender System in IoT”, 2015 5th International Conference on the Internet of Things (IoT).
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