Machine learning in the Internet of Things: A semantic-enhanced approach-Reference-Cited by-同舟云学术

Machine learning in the Internet of Things: A semantic-enhanced approach

Published:2018-12-28 Issue:1 Volume:10 Page:183-204
ISSN:2210-4968
Container-title:Semantic Web
language:
Short-container-title:SW

Author:

Ruta Michele¹,Scioscia Floriano¹,Loseto Giuseppe¹,Pinto Agnese¹,Di Sciascio Eugenio¹

Affiliation:

1. Department of Electrical and Information Engineering, Polytechnic University of Bari, via E. Orabona 4, I-70125, Bari, Italy

Publisher

IOS Press

Subject

Computer Networks and Communications,Computer Science Applications,Information Systems

Reference60 articles.

1. Unified IoT ontology to enable interoperability and federation of testbeds

2. Instance-based learning algorithms;Aha;Machine Learning,1991

3. Stream reasoning and complex event processing in ETALIS;Anicic;Semantic web,2012

4. F. Baader, D. Calvanese, D.L. McGuinness, D. Nardi and P. Patel-Schneider, The Description Logic Handbook, Cambridge University Press, New York, NY, USA, 2002, ISBN 0-521-78176-0.

5. OGC® Sensor Web Enablement: Overview and High Level Architecture

Cited by 33 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Expanding the cloud-to-edge continuum to the IoT in serverless federated learning;Future Generation Computer Systems;2024-06

2. Enhancing IoT Intelligence: A Transformer-based Reinforcement Learning Methodology;2024 International Wireless Communications and Mobile Computing (IWCMC);2024-05-27

3. Complex Event Processing in Web Streams with Ontology-Based Abstraction Layers for Smart City Frameworks;2024 International Conference on Trends in Quantum Computing and Emerging Business Technologies;2024-03-22

4. Aggressive Driver Behavior Detection Using Multi-Label Classification;2024 18th International Conference on Ubiquitous Information Management and Communication (IMCOM);2024-01-03

5. A Framework for Automatic Knowledge Base Generation from Observation Data Sets;Communications in Computer and Information Science;2024