Smart City Gnosys

Smart city article details

Title Data Mining Algorithms For Smart Cities: A Bibliometric Analysis
ID_Doc 17263
Authors Kousis A.; Tjortjis C.
Year 2021
Published Algorithms, 14, 8
DOI http://dx.doi.org/10.3390/a14080242
Abstract Smart cities connect people and places using innovative technologies such as Data Mining (DM), Machine Learning (ML), big data, and the Internet of Things (IoT). This paper presents a bibliometric analysis to provide a comprehensive overview of studies associated with DM technologies used in smart cities applications. The study aims to identify the main DM techniques used in the context of smart cities and how the research field of DM for smart cities evolves over time. We adopted both qualitative and quantitative methods to explore the topic. We used the Scopus database to find relative articles published in scientific journals. This study covers 197 articles published over the period from 2013 to 2021. For the bibliometric analysis, we used the Biliometrix library, developed in R. Our findings show that there is a wide range of DM technologies used in every layer of a smart city project. Several ML algorithms, supervised or unsupervised, are adopted for operating the instrumentation, middleware, and application layer. The bibliometric analysis shows that DM for smart cities is a fast-growing scientific field. Scientists from all over the world show a great interest in researching and collaborating on this interdisciplinary scientific field.
Author Keywords Bibliometrics; Big data; Data mining; Machine learning; Smart cities


Similar Articles


Id Similarity Authors Title Published
10423 View0.938Gupta A.; Gupta S.; Memoria M.; Kumar R.; Kumar S.; Singh D.; Tyagi S.; Ansari N.Artificial Intelligence And Smart Cities: A Bibliometric Analysis2022 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing, COM-IT-CON 2022 (2022)
12040 View0.931Liu Z.; Pan D.; Zhong J.; Huang H.Big Data And Data Mining Technologies Driving Smart City Construction: A Bibliometrics Study From 2014 To 2024Proceedings of 2024 4th International Conference on Computational Modeling, Simulation and Data Analysis, CMSDA 2024 (2025)
35974 View0.923Luan B.; Feng X.Machine Learning For Resilient And Sustainable Cities: A Bibliometric Analysis Of Smart Urban TechnologiesBuildings, 15, 7 (2025)
17266 View0.922de Souza J.T.; de Francisco A.C.; Piekarski C.M.; do Prado G.F.Data Mining And Machine Learning To Promote Smart Cities: A Systematic Review From 2000 To 2018Sustainability (Switzerland), 11, 4 (2019)
21928 View0.922Morik K.; Giannotti F.; González M.; Katakis I.Editor’S Note: Special Section On Data Mining For Smart CitiesData Mining and Knowledge Discovery, 32, 3 (2018)
40125 View0.917Hurbean L.; Danaiata D.; Militaru F.; Dodea A.-M.; Negovan A.-M.Open Data Based Machine Learning Applications In Smart Cities: A Systematic Literature ReviewElectronics (Switzerland), 10, 23 (2021)
5056 View0.916Wang J.; Wang M.; Song Y.A Study On Smart City Research Activity Using Bibliometric And Natural Language Processing MethodsACM International Conference Proceeding Series (2021)
50087 View0.914Soomro K.; Bhutta M.N.M.; Khan Z.; Tahir M.A.Smart City Big Data Analytics: An Advanced ReviewWiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 9, 5 (2019)
50152 View0.913Sarker I.H.Smart City Data Science: Towards Data-Driven Smart Cities With Open Research IssuesInternet of Things (Netherlands), 19 (2022)
49427 View0.91Bhardwaj V.; Anooja A.; Vermani L.S.; Sunita; Dhaliwal B.K.Smart Cities And The Iot: An In-Depth Analysis Of Global Research Trends And Future DirectionsDiscover Internet of Things, 4, 1 (2024)