Data mining in IoT: data analysis for a new paradigm on the Internet
Paper
Paper/Presentation Title | Data mining in IoT: data analysis for a new paradigm on the Internet |
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Presentation Type | Paper |
Authors | Wlodarczak, Peter (Author), Ally, Mustafa (Author) and Soar, Jeffrey (Author) |
Journal or Proceedings Title | Proceedings of the 2017 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2017) |
ERA Conference ID | 60342 |
Number of Pages | 4 |
Year | 2017 |
Place of Publication | New York, United States |
ISBN | 9781450349512 |
Digital Object Identifier (DOI) | https://doi.org/10.1145/3106426.3115866 |
Web Address (URL) of Paper | https://dl.acm.org/citation.cfm?doid=3106426.3115866 |
Conference/Event | 2017 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2017) |
IEEE/WIC/ACM International Conference on Web Intelligence (WI) | |
Event Details | 2017 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2017) Event Date 23 to end of 26 Aug 2017 Event Location Leipzig, Germany |
Event Details | IEEE/WIC/ACM International Conference on Web Intelligence (WI) WI |
Abstract | This paper provides an overview on Data Mining (DM) technologies for the Internet of Things (IoT). IoT has become an active area of research, since IoT promises among other to improve quality of live and safety in Smart Cities, to make resource supply and waste management |
Keywords | Internet of Things, data mining, machine learning, predictive analytics, Smart City |
ANZSRC Field of Research 2020 | 460609. Networking and communications |
Public Notes | Copyright © 2017 by the Association for Computing Machinery, Inc. Permanent restricted access to PV in accordance with the copyright policy of the publisher. |
Byline Affiliations | School of Management and Enterprise |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q4746/data-mining-in-iot-data-analysis-for-a-new-paradigm-on-the-internet
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