PERTANIKA JOURNAL OF SOCIAL SCIENCES AND HUMANITIES

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• Cao, B., Liu, J., Wen, Y., Li, H., Xiao, Q., & Chen, J. (2019). QoS-aware service recommendation based on relational topic model and factorization machines for IoT Mashup applications. Journal of Parallel and Distributed Computing, 132, 177-189. https://doi.org/10.1016/j.jpdc.2018.04.002

• Cha, S., Ruiz, M. P., Wachowicz, M., Tran, L. H., Cao, H., & Maduako, I. (2017). The role of an IoT platform in the design of real-time recommender systems. In 2016 IEEE 3rd world forum on Internet of things (WF-iot) (pp. 448-453). IEEE Publishing. https://doi.org/10.1109/WF-IoT.2016.7845469

• Chaudhari, S., Azaria, A., & Mitchell, T. (2017). An entity graph based Recommender System. AI Communications, 30(2), 141-149. https://doi.org/10.3233/AIC-170728

• Chirila, S., Lemnaru, C., & Dinsoreanu, M. (2016). Semantic-based IoT device discovery and recommendation mechanism. In 2016 IEEE 12th International Conference on Intelligent Computer Communication and Processing (ICCP) (pp. 111-116). IEEE Publishing. https://doi.org/10.1109/ICCP.2016.7737131

• Choi, S. M., Lee, H., Han, Y. S., Man, K. L., & Chong, W. K. (2015). A Recommendation Model Using the Bandwagon Effect for E-Marketing Purposes in IoT. International Journal of Distributed Sensor Networks, 11(7), Article 475163. https://doi.org/10.1155/2015/475163

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• Di Martino, S., & Rossi, S. (2016). An architecture for a mobility recommender system in smart cities. Procedia Computer Science, 58, 425-430. https://doi.org/10.1016/j.procs.2016.09.066

• Elmisery, A. M., Rho, S., & Sertovic, M. (2017). Privacy aware group based recommender system in multimedia services. Multimedia Tools and Applications, 76(24), 26103-26127. https://doi.org/10.1007/s11042-017-4950-0

• Erdeniz, S. P., Menychtas, A., Maglogiannis, I., Felfernig, A., & Tran, T. N. T. (2019). Recommender systems for IoT enabled quantified-self applications. Evolving Systems, 11(2), 291-304. https://doi.org/10.1007/s12530-019-09302-8

• Felfernig, A., Erdeniz, S. P., Jeran, M., Akcay, A., Azzoni, P., Maiero, M., & Doukas, C. (2017). Recommendation technologies for IoT edge devices. Procedia Computer Science, 110, 504-509. https://doi.org/10.1016/j.procs.2017.06.135

• Felfernig, A., Polat-Erdeniz, S., Uran, C., Reiterer, S., Atas, M., Tran, T. N. T., Azzoni, P., Kiraly, C., & Dolui, K. (2019). An overview of recommender systems in the Internet of things. Journal of Intelligent Information Systems, 52(2), 285-309. https://doi.org/10.1007/s10844-018-0530-7

• Forestiero, A. (2017). Multi-Agent recommendation system in Internet of things. In 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID) (pp. 772-775). IEEE Publishing. https://doi.org/10.1109/CCGRID.2017.123

• Forouzandeh, S., Aghdam, A. R., Barkhordari, M., & Fahimi, A. (2017). Recommender system for users of Internet of Things (IOT). International Journal of Computer Science and Network Security, 17(8), 46-51.

• Franco, D. A. I. (2017). A recommender system for automation rules in the Internet of Things (MSc Thesis). Instituto Superior Técnico, Portugal.

• Frey, R. M., Xu, R., & Ilic, A. (2015). A Novel Recommender System in IoT. In 2015 5th International Conference on the Internet of Things (IOT 2015). IEEE Publishing. https://doi.org/10.3929/ethz-a-010561395

• Gladence, L. M., Anu, V. M., Rathna, R., & Brumancia, E. (2020). Recommender system for home automation using IoT and artificial intelligence. Journal of Ambient Intelligence and Humanized Computing, 1-9. https://doi.org/10.1007/s12652-020-01968-2

• Guo, Z., & Wang, H. (2020). A deep graph neural network-based mechanism for social recommendations. IEEE Transactions on Industrial Informatics, 3203(c), 1-1. https://doi.org/10.1109/tii.2020.2986316

• HamlAbadi, K. G., Saghiri, A. M., Vahdati, M., TakhtFooladi, M. D., & Meybodi, M. R. (2018). A framework for cognitive recommender systems in the Internet of Things (IoT). In 2017 IEEE 4th international conference on knowledge-based engineering and innovation (KBEI) (pp. 0971-0976). IEEE Publishing. https://doi.org/10.1109/KBEI.2017.8324939

• Huang, Z., Xu, X., Ni, J., Zhu, H., & Wang, C. (2019). Multimodal representation learning for recommendation in Internet of Things. IEEE Internet of Things Journal, 6(6), 10675-10685. https://doi.org/10.1109/JIOT.2019.2940709

• Isinkaye, F. O., Folajimi, Y. O., & Ojokoh, B. A. (2015). Recommendation systems: Principles, methods and evaluation. Egyptian Informatics Journal, 16(3), 261-273. https://doi.org/10.1016/j.eij.2015.06.005

• Iwendi, C., Khan, S., Anajemba, J. H., Bashir, A. K., & Noor, F. (2020). Realizing an efficient IoMT-assisted patient diet recommendation system through machine learning model. IEEE Access, 8, 28462-28474. https://doi.org/10.1109/ACCESS.2020.2968537

• Jabeen, F., Maqsood, M., Ghazanfar, M. A., Aadil, F., Khan, S., Khan, M. F., & Mehmood, I. (2019). An IoT based efficient hybrid recommender system for cardiovascular disease. Peer-to-Peer Networking and Applications, 12(5), 1263-1276. https://doi.org/10.1007/s12083-019-00733-3

• Kang, D., Choi, H., Choi, S., & Rhee, W. (2017). SRS : Social Correlation Group based Recommender System for Social IoT Environment. International Journal of Contents, 13(1), 53-61. https://doi.org/10.5392/IJoC.2017.13.1.053

• Kang, D., Choi, H., & Rhee, W. (2016). Social Correlation Group Generation Mechanism in Social IoT Environment. In 2016 Eighth International Conference on Ubiquitous and Future Networks (ICUFN) (pp. 514-519). IEEE Publishing. https://doi.org/10.1109/ICUFN.2016.7537086

• Kolbe, N., Kubler, S., Robert, J., Le Traon, Y., & Zaslavsky, A. (2019). Linked vocabulary recommendation tools for Internet of things: A survey. ACM Computing Surveys, 51(6), 1-31. https://doi.org/10.1145/3284316

• Kwon, J., & Kim, S. (2016). Study on Recommendation in Internet of Things Environment. In 2015 7th International Conference on Multimedia, Computer Graphics and Broadcasting (MulGraB) (pp. 13-14). IEEE Publishing. https://doi.org/10.1109/MulGraB.2015.13

• Lee, J. S., & Ko, I. Y. (2016). Service recommendation for user groups in Internet of things environments using member organization-based group similarity measures. In 2016 IEEE international conference on web services (ICWS) (pp. 276-283). IEEE Publishing. https://doi.org/10.1109/ICWS.2016.43

• Lee, K., Lee, Y. S., & Nam, Y. (2019). A novel approach of making better recommendations by revealing hidden desires and information curation for users of Internet of things. Multimedia Tools and Applications, 78(3), 3183-3201. https://doi.org/10.1007/s11042-018-6084-4

• Lee, K., & Lee, K. (2015). Escaping your comfort zone: A graph-based recommender system for finding novel recommendations among relevant items. Expert Systems with Applications, 42(10), 4851-4858. https://doi.org/10.1016/j.eswa.2014.07.024

• Mashal, I., Alsaryrah, O., & Chung, T. Y. (2016). Analysis of recommendation algorithms for Internet of Things. In 2016 IEEE Wireless Communications and Networking Conference (pp. 1-6). IEEE Publishing. https://doi.org/10.1109/WCNC.2016.7564667

• Mashal, I., Alsaryrah, O., Chung, T. Y., & Yuan, F. C. (2020). A multi-criteria analysis for an Internet of things application recommendation system. Technology in Society, 60, Article 101216. https://doi.org/10.1016/j.techsoc.2019.101216

• Mashal, I., Chung, T. Y., & Alsaryrah, O. (2015). Toward service recommendation in Internet of Things. In 2015 Seventh International Conference on Ubiquitous and Future Networks (pp. 328-331). IEEE Publishing. https://doi.org/10.1109/ICUFN.2015.7182559

• Matsui, K., & Choi, H. (2017). A recommendation system with secondary usage of HEMS data for products based on IoT technology. In 2017 International Symposium on Networks, Computers and Communications (ISNCC) (pp. 1-6). IEEE Publishing. https://doi.org/10.1109/ISNCC.2017.8071982

• Milano, S., Taddeo, M., & Floridi, L. (2020). Recommender systems and their ethical challenges. AI & Society, 35(4), 957-967. https://doi.org/10.1007/s00146-020-00950-y

• Mohammadi, V., Rahmani, A. M., Darwesh, A. M., & Sahafi, A. (2019). Trust-based recommendation systems in Internet of Things: a systematic literature review. Human-centric Computing and Information Sciences, 9(1), 1-61. https://doi.org/10.1186/s13673-019-0183-8

• Muñoz-Organero, M., Ramíez-González, G. A., Muñoz-Merino, P. J., & Delgado Kloos, C. (2010). A collaborative recommender system based on space-time similarities. IEEE Pervasive Computing, 9(3), 81-87. https://doi.org/10.1109/MPRV.2010.56

• Musto, C., Lops, P., Basile, P., de Gemmis, M., & Semeraro, G. (2016). Semantics-aware graph-based recommender systems exploiting linked open data. In Proceedings of the 2016 conference on user modeling adaptation and personalization (pp. 229-237). Association for Computing Machinery. https://doi.org/10.1145/2930238.2930249

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• Noirie, L., Le Pallec, M., & Ammar, N. (2017). Towards automated IoT service recommendation. In 2017 20th Conference on Innovations in Clouds, Internet and Networks (ICIN) (pp. 103-106). IEEE Publishing. https://doi.org/10.1109/ICIN.2017.7899397

• Ouhbi, B., Frikh, B., Zemmouri, E., & Abbad, A. (2018). Deep learning based recommender system. In 2018 IEEE 5th International Congress on Information Science and Technology (CiSt) (pp. 161-166). https://doi.org/10.1109/CIST.2018.8596492

• Palaiokrassas, G., Karlis, I., Litke, A., Charlaftis, V., & Varvarigou, T. (2017). An IoT architecture for personalized recommendations over big data oriented applications. In 2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC) (Vol. 2, pp. 475-480). IEEE Publishing. https://doi.org/10.1109/COMPSAC.2017.59

• Pratibha, & Kaur, P. D. (2018). Towards incorporating context awareness to recommender systems in Internet of things. Smart Innovation, Systems and Technologies, 79, 771-780. https://doi.org/10.1007/978-981-10-5828-8_73

• Ravi, L., Vairavasundaram, S., Palani, S., & Devarajan, M. (2019). Location-based personalized recommender system in the Internet of cultural things. Journal of Intelligent & Fuzzy Systems, 36(5), 4141-4152. https://doi.org/10.3233/JIFS-169973

• Roopa, M. S., Pattar, S., Buyya, R., Venugopal, K. R., Iyengar, S. S., & Patnaik, L. M. (2019). Social Internet of Things (SIoT): Foundations, thrust areas, systematic review and future directions. Computer Communications, 139(September 2018), 32-57. https://doi.org/10.1016/j.comcom.2019.03.009

• Sawant, S. D., Sonawane, K. V., Jagani, T., & Chaudhari, A. N. (2017). Representation of recommender system in IoT using cyber physical techniques. In 2017 International conference of Electronics, Communication and Aerospace Technology (ICECA) (Vol. 2, pp. 372-375). IEEE Publishing. https://doi.org/10.1109/ICECA.2017.8212836

• Saghiri, A. M., Vahdati, M., Gholizadeh, K., Meybodi, M. R., Dehghan, M., & Rashidi, H. (2018). A framework for cognitive Internet of Things based on blockchain. In 2018 4th International Conference on Web Research (ICWR) (pp. 138-143). IEEE Publishing. https://doi.org/10.1109/ICWR.2018.8387250

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